# Wrong intent and entity detected if examples contains numbers as digit sequences

**URL:** <https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860>\
**Category:** Getting Started with Rasa\
**Created:** [August 13, 2021, 3:05pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860 "2021-08-13T15:05:23Z")\
**Posts on this page:** 11\
**Page:** 1

<div class="post-metadata">

**Author:** ![solyarisoftware](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/solyarisoftware/32/8464_2.png) [@solyarisoftware](https://forum.rasa.com/u/solyarisoftware)\
**Post date:** [August 13, 2021, 3:05pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/1 "2021-08-13T15:05:23Z")

</div>

I have two different intents to capture body temperature and oxygen saturation values:

- Intent: `body_temperature_data` (containing `body_temperature` custom entity)
- Intent: `oxygen_saturation_data` (containing `oxygen_saturation` custom entity)

Here below a `data/intents.yml` excerpt:

```yaml
  - intent: body_temperature_data
    examples: |
      - sto bene
      - niente febbre
      - normale
      - sono senza febbre
      - non ho febbre
      - non mi sento la febbre
      - ho qualche linea
      - ho la febbre
      - credo di avere la febbre
      - mi sento un po di febbre
      - mi sento caldo
      - poca
      - molto poca
      - bassa
      - alta
      - molto alta
      - [35](body_temperature)
      - [35.5](body_temperature)
      - [35.6](body_temperature)
      - [35.7](body_temperature)
      - [35.8](body_temperature)
      - [35.9](body_temperature)
      - [35 e 9](body_temperature)
      - [35,9](body_temperature)
      - [36](body_temperature)
      - [36.0](body_temperature)
      - [36.1](body_temperature)
      - [36.2](body_temperature)
      - [36.3](body_temperature)
      - [36.4](body_temperature)
      - [36.5](body_temperature)
      - [36.6](body_temperature)
      - [36.7](body_temperature)
      - [36.8](body_temperature)
      - [36.9](body_temperature)
      - [36 e 7](body_temperature)
      - [36,9](body_temperature)
      - [37](body_temperature)
      - [37.0](body_temperature)
      - [37.1](body_temperature)
      - [37.2](body_temperature)
      - [37.3](body_temperature)
      - [37.4](body_temperature)
      - [37.5](body_temperature)
      - [37.6](body_temperature)
      - [37.7](body_temperature)
      - [37.8](body_temperature)
      - [37.9](body_temperature)
      - [37,2](body_temperature)
      - [37.5](body_temperature)
      - [37 , 6](body_temperature)
      - [37 . 6](body_temperature)
      - [38](body_temperature)
      - [38.0](body_temperature)
      - [38.1](body_temperature)
      - [38.2](body_temperature)
      - [38.3](body_temperature)
      - [38.4](body_temperature)
      - [38.5](body_temperature)
      - [38.6](body_temperature)
      - [38.7](body_temperature)
      - [38.8](body_temperature)
      - [38.9](body_temperature)
      - [38 , 1](body_temperature)
      - [38 . 2](body_temperature)
      - [39](body_temperature)
      - [39,1](body_temperature)
      - [39.1](body_temperature)
      - [39.2](body_temperature)
      - [39.3](body_temperature)
      - [39.5](body_temperature)
      - [39.6](body_temperature)
      - [39.7](body_temperature)
      - [39.8](body_temperature)
      - [39.9](body_temperature)
      - [40](body_temperature)
      - [41](body_temperature)
      - [trentacinque](body_temperature)
      - [trentasei](body_temperature)
      - [trentasei e otto](body_temperature)
      - [trentasette](body_temperature)
      - [trentasette emmezzo](body_temperature)
      - [trentasette e mezzo](body_temperature)
      - [trentasette punto otto](body_temperature)
      - [trentasette e quattro lineette](body_temperature)
      - [trentasette e 6 linee](body_temperature)
      - [trentasette virgola sei](body_temperature)
      - [trentasette punto sette](body_temperature)
      - [trentasette punto otto](body_temperature)
      - [trentotto](body_temperature)
      - [trentotto punto uno](body_temperature)
      - [trentotto e 2 linee](body_temperature)
      - [trentotto e due](body_temperature)
      - [trentotto punto tre](body_temperature)
      - [trentotto e quattro](body_temperature)
      - [trentotto virgola quattro](body_temperature)
      - [trentotto emmezzo](body_temperature)
      - [trentanove](body_temperature)
      - [trentanove e due](body_temperature)
      - [trentanove emmezzo](body_temperature)
      - [quaranta](body_temperature)
      - [quarantuno](body_temperature)

  - intent: oxygen_saturation_data
    examples: |
      - [70](oxygen_saturation)
      - [71](oxygen_saturation)
      - [72](oxygen_saturation)
      - [73](oxygen_saturation)
      - [74](oxygen_saturation)
      - [75](oxygen_saturation)
      - [76](oxygen_saturation)
      - [77 e 9](oxygen_saturation)
      - [78,7](oxygen_saturation)
      - [79](oxygen_saturation)
      - [80](oxygen_saturation)
      - [80.5](oxygen_saturation)
      - [81](oxygen_saturation)
      - [81.6](oxygen_saturation)
      - [82](oxygen_saturation)
      - [82.4](oxygen_saturation)
      - [83](oxygen_saturation)
      - [83.7](oxygen_saturation)
      - [84](oxygen_saturation)
      - [84.1](oxygen_saturation)
      - [85](oxygen_saturation)
      - [85.2](oxygen_saturation)
      - [86](oxygen_saturation)
      - [86.9](oxygen_saturation)
      - [87](oxygen_saturation)
      - [87.8](oxygen_saturation)
      - [88](oxygen_saturation)
      - [88.0](oxygen_saturation)
      - [88.1](oxygen_saturation)
      - [89.0](oxygen_saturation)
      - [89](oxygen_saturation)
      - [89.7](oxygen_saturation)
      - [90](oxygen_saturation)
      - [90.0](oxygen_saturation)
      - [90.1](oxygen_saturation)
      - [90.2](oxygen_saturation)
      - [90.3](oxygen_saturation)
      - [90.4](oxygen_saturation)
      - [90.5](oxygen_saturation)
      - [90.6](oxygen_saturation)
      - [90.7](oxygen_saturation)
      - [90.8](oxygen_saturation)
      - [90.9](oxygen_saturation)
      - [91](oxygen_saturation)
      - [91.6](oxygen_saturation)
      - [92](oxygen_saturation)
      - [92.9](oxygen_saturation)
      - [93](oxygen_saturation)
      - [93.8](oxygen_saturation)
      - [94](oxygen_saturation)
      - [94.5](oxygen_saturation)
      - [95](oxygen_saturation)
      - [95.4](oxygen_saturation)
      - [96](oxygen_saturation)
      - [96.7](oxygen_saturation)
      - [97](oxygen_saturation)
      - [97.5](oxygen_saturation)
      - [98](oxygen_saturation)
      - [98.4](oxygen_saturation)
      - [99](oxygen_saturation)
      - [99 e 1](oxygen_saturation)
      - [99.0](oxygen_saturation)
      - [99.9](oxygen_saturation)
      - [100](oxygen_saturation)
      - [settanta](oxygen_saturation)
      - [settantuno](oxygen_saturation)
      - [settantadue](oxygen_saturation)
      - [settantatre](oxygen_saturation)
      - [settantaquattro](oxygen_saturation)
      - [settantacinque](oxygen_saturation)
      - [settantasei](oxygen_saturation)
      - [settantasette](oxygen_saturation)
      - [settantotto](oxygen_saturation)
      - [settantanove](oxygen_saturation)
      - [ottanta](oxygen_saturation)
      - [ottantuno](oxygen_saturation)
      - [ottantadue](oxygen_saturation)
      - [ottantatre](oxygen_saturation)
      - [ottantatre punto cinque](oxygen_saturation)
      - [ottantatre punto sei](oxygen_saturation)
      - [ottantaquattro emmezzo](oxygen_saturation)
      - [ottantaquattro e sei](oxygen_saturation)
      - [ottantaquattro punto sette](oxygen_saturation)
      - [ottantaquattro punto sei](oxygen_saturation)
      - [ottantaquattro punto nove](oxygen_saturation)
      - [ottantacinque](oxygen_saturation)
      - [ottantacinque punto cinque](oxygen_saturation)
      - [ottantacinque e quattro](oxygen_saturation)
      - [ottantasei](oxygen_saturation)
      - [ottantasette](oxygen_saturation)
      - [ottantotto](oxygen_saturation)
      - [ottantanove](oxygen_saturation)
      - [novanta](oxygen_saturation)
      - [novanta punto tre](oxygen_saturation)
      - [novanta punto otto](oxygen_saturation)
      - [novantuno](oxygen_saturation)
      - [novantuno punto cinque](oxygen_saturation)
      - [novantuno punto nove](oxygen_saturation)
      - [novantadue](oxygen_saturation)
      - [novantatre](oxygen_saturation)
      - [novantatre e sei](oxygen_saturation)
      - [novantatre punto sette](oxygen_saturation)
      - [novantatre virgola otto](oxygen_saturation)
      - [novantatre e due](oxygen_saturation)
      - [novantatre punto uno](oxygen_saturation)
      - [novantatre virgola nove](oxygen_saturation)
      - [novantaquattro](oxygen_saturation)
      - [novantaquattro virgola due](oxygen_saturation)
      - [novantaquattro virgola otto](oxygen_saturation)
      - [novantacinque](oxygen_saturation)
      - [novantacinque e cinque](oxygen_saturation)
      - [novantacinque punto cinque](oxygen_saturation)
      - [novantasei](oxygen_saturation)
      - [novantasei e uno](oxygen_saturation)
      - [novantasei e cinque](oxygen_saturation)
      - [novantasette](oxygen_saturation)
      - [novantasette e due](oxygen_saturation)
      - [novantasette e sei](oxygen_saturation)
      - [novantotto](oxygen_saturation)
      - [novantotto e cinque](oxygen_saturation)
      - [novantanove](oxygen_saturation)
      - [novantanove emmezzo](oxygen_saturation)
      - [cento](oxygen_saturation)

```

As the examples show, I would like to get entities values (and afterward slots in a form) expressed as

- numbers as digits (`35.5`), possibly texted by user on a chat messaging channel
- numbers as letters (`trentacinque punto cinque`), possibly inputed via speech so the speech recognition engine returns generally a literal transcript for numbers.

See what happens if I test the RASA NLU:

```json
$ rasa shell nlu --quiet
NLU model loaded. Type a message and press enter to parse it.
Next message:
90.3
{
  "text": "90.3",
  "intent": {
    "id": -6401318193538980427,
    "name": "body_temperature_data",
    "confidence": 0.7580949664115906
  },
  "entities": [
    {
      "entity": "body_temperature",
      "start": 0,
      "end": 4,
      "confidence_entity": 0.7051703929901123,
      "value": "90.3",
      "extractor": "DIETClassifier"
    }
  ],
  "intent_ranking": [
    {
      "id": -6401318193538980427,
      "name": "body_temperature_data",
      "confidence": 0.7580949664115906
    },
    {
      "id": 8358940020600517004,
      "name": "oxygen_saturation_data",
      "confidence": 0.18363729119300842
    },
    {
      "id": -860430617479998517,
      "name": "mood_unhappy",
      "confidence": 0.010874141938984394
    },
Next message:
novanta punto tre
{
  "text": "novanta punto tre",
  "intent": {
    "id": 8358940020600517004,
    "name": "oxygen_saturation_data",
    "confidence": 0.9999997615814209
  },
  "entities": [
    {
      "entity": "oxygen_saturation",
      "start": 0,
      "end": 17,
      "confidence_entity": 0.9956320524215698,
      "value": "novanta punto tre",
      "extractor": "DIETClassifier"
    }
  ],
  "intent_ranking": [
    {
      "id": 8358940020600517004,
      "name": "oxygen_saturation_data",
      "confidence": 0.9999997615814209
    },
    {
      "id": -860430617479998517,
      "name": "mood_unhappy",
      "confidence": 4.465892544658345e-08
    },

```

So what happens is that if numbers are inserted as words/letters, RASA classify correctly intent `oxygen_saturation_data` and entity `oxygen_saturation`. So far, so good.

But If I insert numbers by digits (e.g. `90.3`), the intent and entity are wrong classified.

This surprise me because the examples set of two intents `body_temperature` and `oxygen_saturation` are two completely separated set of texts!

### My question is WHY intent/entity is wrongly classified?

* * *

BTW, I tried to add quotation marks in examples:

```
  - ['35.5'](oxygen_saturation)

```

Instead of:

```
  - [35.5](oxygen_saturation)

```

but this rise this error/warning at train time:

> /home/giorgio/.local/lib/python3.8/site-packages/rasa/shared/utils/io.py:97: UserWarning: Misaligned entity annotation in message ‘‘35.5’’ with intent ‘body\_temperature\_data’. Make sure the start and end values of entities ([(0, 6, “‘35.5’”)]) in the training data match the token boundaries ([(0, 5, “'35.5”)]). Common causes:
> 
> 1. entities include trailing whitespaces or punctuation
> 2. the tokenizer gives an unexpected result, due to languages such as Chinese that don’t use whitespace for word separation More info at [Training Data Format | Rasa Documentation](https://rasa.com/docs/rasa/training-data-format#nlu-training-data)

My doubt is about having numbers (e.g. floating numbers as digits strings as `35.5`) as entities (and intents examples). Could be this the reason why RASA NLU fails (see rasa shell nlu report above)?

Any idea?

```bash
$ cat config.yml

```

```yaml
# Configuration for Rasa NLU.
# https://rasa.com/docs/rasa/nlu/components/
language: it

pipeline:

  # pip3 install rasa[spacy]
  # python3 -m spacy download it_core_news_sm
  # python3 -m spacy download it_core_news_lg
  # https://rasa.com/docs/rasa/components#spacynlp
  - name: "SpacyNLP"
    # language model to load
    # italian large model: it_core_news_lg
    # italian small model: it_core_news_sm
    model: "it_core_news_sm"
    # when retrieving word vectors, this will decide if the casing
    # of the word is relevant. E.g. `hello` and `Hello` will
    # retrieve the same vector, if set to `False`. For some
    # applications and models it makes sense to differentiate
    # between these two words, therefore setting this to `True`.
    case_sensitive: false

  - name: WhitespaceTokenizer
  - name: RegexFeaturizer
  - name: LexicalSyntacticFeaturizer
  - name: CountVectorsFeaturizer
  - name: CountVectorsFeaturizer
    analyzer: "char_wb"
    min_ngram: 1
    max_ngram: 4

  - name: DIETClassifier
    epochs: 100
    constrain_similarities: true

  - name: EntitySynonymMapper
  - name: ResponseSelector
    epochs: 100
    constrain_similarities: true

  - name: FallbackClassifier
    threshold: 0.3
    ambiguity_threshold: 0.1

policies:

```

Thanks

---

<div class="post-metadata">

**Author:** ![nik202](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/nik202/32/16098_2.png) [@nik202](https://forum.rasa.com/u/nik202)\
**Post date:** [August 13, 2021, 4:24pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/2 "2021-08-13T16:24:28Z")

</div>

@solyarisoftware Hi, nice question and query! What is your slot type of `oxygen_saturation` I guess text? just checking.

---

<div class="post-metadata">

**Author:** ![solyarisoftware](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/solyarisoftware/32/8464_2.png) [@solyarisoftware](https://forum.rasa.com/u/solyarisoftware)\
**Post date:** [August 13, 2021, 6:46pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/3 "2021-08-13T18:46:41Z")

</div>

Yes @nik202, thanks

```auto
entities:
  - body_temperature
  - oxygen_saturation
 
slots:
  body_temperature:
    type: text
    auto_fill: false
  oxygen_saturation:
    type: text
    auto_fill: false
 
forms:
  health_monitoring_form:
    required_slots:
    ⦙ body_temperature:
    ⦙ - type: from_text
    ⦙ ⦙ intent_name: body_temperature_data
    ⦙ oxygen_saturation:
    ⦙ - type: from_text
    ⦙ ⦙ intent_name: oxygen_saturation_data

```

BTW, in the form, as you see, slots refer to intents… that’s solve the issue but it’s a workaround I guess, whereas the default choice would be to get slots from corresponding entities. but in that way I got problems as you imagine.

Thanks for the help

---

<div class="post-metadata">

**Author:** ![nik202](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/nik202/32/16098_2.png) [@nik202](https://forum.rasa.com/u/nik202)\
**Post date:** [August 13, 2021, 7:01pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/4 "2021-08-13T19:01:18Z")

</div>

@solyarisoftware great, you solved the query 👏.

---

<div class="post-metadata">

**Author:** ![solyarisoftware](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/solyarisoftware/32/8464_2.png) [@solyarisoftware](https://forum.rasa.com/u/solyarisoftware)\
**Post date:** [August 13, 2021, 9:27pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/5 "2021-08-13T21:27:09Z")

</div>

but the initial problem (intent/entity confusion) is still there.

---

<div class="post-metadata">

**Author:** ![nik202](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/nik202/32/16098_2.png) [@nik202](https://forum.rasa.com/u/nik202)\
**Post date:** [August 13, 2021, 9:30pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/6 "2021-08-13T21:30:38Z")

</div>

@solyarisoftware slot type float? have tried that? or type any?

---

<div class="post-metadata">

**Author:** ![solyarisoftware](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/solyarisoftware/32/8464_2.png) [@solyarisoftware](https://forum.rasa.com/u/solyarisoftware)\
**Post date:** [August 13, 2021, 9:46pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/7 "2021-08-13T21:46:10Z")

</div>

I’d exclude type `float` because I wish to take vales in numeric and literal form, e.g.

- `93.4`
- `ninety three point four`

but tomorrow I’ll try type `any`. thanks

So having set type `text`… this doesn’t allow RASA to classify correctly numbers? Weird 🙄

---

<div class="post-metadata">

**Author:** ![nik202](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/nik202/32/16098_2.png) [@nik202](https://forum.rasa.com/u/nik202)\
**Post date:** [August 13, 2021, 9:46pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/8 "2021-08-13T21:46:44Z")

</div>

@solyarisoftware good luck!

---

<div class="post-metadata">

**Author:** ![solyarisoftware](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/solyarisoftware/32/8464_2.png) [@solyarisoftware](https://forum.rasa.com/u/solyarisoftware)\
**Post date:** [August 14, 2021, 10:09am UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/9 "2021-08-14T10:09:10Z")

</div>

BTW, I think RASA NLU wrong intent/entity prediction is NOT related to slots configuration. `rasa shell nlu’ report seems to suggest that the issue is just related to NLU problems with numbers. 🤔

---

<div class="post-metadata">

**Author:** ![solyarisoftware](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/solyarisoftware/32/8464_2.png) [@solyarisoftware](https://forum.rasa.com/u/solyarisoftware)\
**Post date:** [August 15, 2021, 4:24pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/10 "2021-08-15T16:24:09Z")

</div>

I maybe solved the issue. Results are now absolutely satisying (see rasa shell nlu tests at the end).

What solved has been

- defining custom entities `body_temperature` and `oxygen_saturation` as lookup lists. See file `data/entities.yml’
- updating intents `body_temperature_data` and `oxygen_saturation_data` to contains more examples an variety of entities.

So I understand that the ENTITIES examples training don’t work if I put these examples inside the INTENTS examples. At list not only…

What is also not clear to me is this: following RASA docs, entities lookup tables are managed as regexp lists… so I do not full understand how the RASA DIETClassifier instead is able to classify correctly bad written entities (mispelled, etc.)

$ cat domain.yml (excerpt)

```auto
version: "2.0"

intents:

  # patient_monitoring application specific intents
  - health_monitoring_request

  - body_temperature_data:
      use_entities:
        - body_temperature

  - oxygen_saturation_data:
      use_entities:
        - oxygen_saturation

```

$ cat data/entities.yml (excerpt)

```auto
version: "2.0"

nlu:

  - lookup: body_temperaturea
    examples: |
      - 35
      - 35.0
      - 35.5
      - 35.5
      - 35.6
      - 35.7
      - 35.8
      - 35.9
      - 36
      - 36.0
      - 36.1
      - 36.2
      - 36.3
      - 36.4
      - 36.5
      - 36.6
      - 36.7
      - 36.8
      - 36.9
      - 37
      - 37.0
      - 37.1
      - 37.2
      - 37.3
      - 37.4
      - 37.5
      - 37.6
      - 37.7
      - 37.8
      - 37.9
      - 38
      - 38.0
      - 38.1
      - 38.2
      - 38.3
      - 38.4
      - 38.5
      - 38.6
      - 38.7
      - 38.8
      - 38.9
      - 39
      - 39.1
      - 39.2
      - 39.3
      - 39.5
      - 39.6
      - 39.7
      - 39.8
      - 39.9
      - 40
      - 41
      - trentacinque
      - trentasei
      - trentasei punto uno
      - trentasei punto due
      - trentasei punto tre
      - trentasei punto quattro
      - trentasei punto cinque
      - trentasei punto sei
      - trentasei punto sette
      - trentasei punto otto
      - trentasei punto nove
      - trentasette
      - trentasette punto uno
      - trentasette punto due
      - trentasette punto tre
      - trentasette punto quattro
      - trentasette punto cinque
      - trentasette punto sei
      - trentasette punto sette
      - trentasette punto otto
      - trentasette punto nove
      - trentasette punto sette
      - trentasette punto otto
      - trentasette punto nove
      - trentotto
      - trentotto punto uno
      - trentotto punto due
      - trentotto punto tre
      - trentotto punto quattro
      - trentotto punto cinque
      - trentotto punto sei
      - trentotto punto sette
      - trentotto punto otto
      - trentotto punto nove
      - trentotto punto sette
      - trentotto punto otto
      - trentotto punto nove
      - trentotto punto uno
      - trentotto punto due
      - trentotto punto tre
      - trentotto punto quattro
      - trentotto punto cinque
      - trentotto punto sei
      - trentotto punto sette
      - trentotto punto otto
      - trentotto punto nove
      - trentotto punto sette
      - trentotto punto otto
      - trentotto punto nove
      - trentanove
      - trentanove punto uno
      - trentanove punto due
      - trentanove punto tre
      - trentanove punto quattro
      - trentanove punto cinque
      - trentanove punto sei
      - trentanove punto sette
      - trentanove punto otto
      - trentanove punto nove
      - trentanove punto sette
      - trentanove punto otto
      - trentanove punto nove
      - quaranta
      - quarantuno

  - lookup: oxygen_saturation
    examples: |
      - 70
      - 71
      - 72
      - 73
      - 74
      - 75
      - 76
      - 77
      - 78
      - 79
      - 80
      - 80.1
      - 80.2
      - 80.3
      - 80.4
      - 80.5
      - 80.6
      - 80.7
      - 80.8
      - 80.9
      - 81
      - 81.1
      - 81.2
      - 81.3
      - 81.4
      - 81.5
      - 81.6
      - 81.7
      - 81.8
      - 81.9
      - 82
      - 82.1
      - 82.2
      - 82.3
      - 82.4
      - 82.5
      - 82.6
      - 82.7
      - 82.8
      - 82.9
      - 83
      - 83.1
      - 83.2
      - 83.3
      - 83.4
      - 83.5
      - 83.6
      - 83.7
      - 83.8
      - 83.9
      - 84
      - 84.1
      - 84.2
      - 84.3
      - 84.4
      - 84.5
      - 84.6
      - 84.7
      - 84.8
      - 84.9
      - 85
      - 85.1
      - 85.2
      - 85.3
      - 85.4
      - 85.5
      - 85.6
      - 85.7
      - 85.8
      - 85.9
      - 86
      - 86.1
      - 86.2
      - 86.3
      - 86.4
      - 86.5
      - 86.6
      - 86.7
      - 86.8
      - 86.9
      - 87
      - 87.1
      - 87.2
      - 87.3
      - 87.4
      - 87.5
      - 87.6
      - 87.7
      - 87.8
      - 87.9
      - 88
      - 88.1
      - 88.2
      - 88.3
      - 88.4
      - 88.5
      - 88.6
      - 88.7
      - 88.8
      - 88.9
      - 89
      - 89.1
      - 89.2
      - 89.3
      - 89.4
      - 89.5
      - 89.6
      - 89.7
      - 89.8
      - 89.9
      - 90
      - 90.1
      - 90.2
      - 90.3
      - 90.4
      - 90.5
      - 90.6
      - 90.7
      - 90.8
      - 90.9
      - 91
      - 91.1
      - 91.2
      - 91.3
      - 91.4
      - 91.5
      - 91.6
      - 91.7
      - 91.8
      - 91.9
      - 92
      - 92.1
      - 92.2
      - 92.3
      - 92.4
      - 92.5
      - 92.6
      - 92.7
      - 92.8
      - 92.9
      - 93
      - 93.1
      - 93.2
      - 93.3
      - 93.4
      - 93.5
      - 93.6
      - 93.7
      - 93.8
      - 93.9
      - 94
      - 94.1
      - 94.2
      - 94.3
      - 94.4
      - 94.5
      - 94.6
      - 94.7
      - 94.8
      - 94.9
      - 95
      - 95.1
      - 95.2
      - 95.3
      - 95.4
      - 95.5
      - 95.6
      - 95.7
      - 95.8
      - 95.9
      - 96
      - 96.1
      - 96.2
      - 96.3
      - 96.4
      - 96.5
      - 96.6
      - 96.7
      - 96.8
      - 96.9
      - 97
      - 97.1
      - 97.2
      - 97.3
      - 97.4
      - 97.5
      - 97.6
      - 97.7
      - 97.8
      - 97.9
      - 98
      - 98.1
      - 98.2
      - 98.3
      - 98.4
      - 98.5
      - 98.6
      - 98.7
      - 98.8
      - 98.9
      - 99
      - 99.1
      - 99.2
      - 99.3
      - 99.4
      - 99.5
      - 99.6
      - 99.7
      - 99.8
      - 99.9
      - 100
      - settanta
      - settantuno
      - settantadue
      - settantatre
      - settantaquattro
      - settantacinque
      - settantasei
      - settantasette
      - settantotto
      - settantanove
      - ottanta
      - ottantuno
      - ottantadue
      - ottantatre
      - ottantatre punto uno
      - ottantatre punto due
      - ottantatre punto tre
      - ottantatre punto quattro
      - ottantatre punto cinque
      - ottantatre punto sei
      - ottantatre punto sette
      - ottantatre punto otto
      - ottantatre punto nove
      - ottantaquattro
      - ottantaquattro punto uno
      - ottantaquattro punto due
      - ottantaquattro punto tre
      - ottantaquattro punto quattro
      - ottantaquattro punto cinque
      - ottantaquattro punto sei
      - ottantaquattro punto sette
      - ottantaquattro punto otto
      - ottantaquattro punto nove
      - ottantacinque
      - ottantacinque punto uno
      - ottantacinque punto due
      - ottantacinque punto tre
      - ottantacinque punto quattro
      - ottantacinque punto cinque
      - ottantacinque punto sei
      - ottantacinque punto sette
      - ottantacinque punto otto
      - ottantacinque punto nove
      - ottantasei
      - ottantasei punto uno
      - ottantasei punto due
      - ottantasei punto tre
      - ottantasei punto quattro
      - ottantasei punto cinque
      - ottantasei punto sei
      - ottantasei punto sette
      - ottantasei punto otto
      - ottantasei punto nove
      - ottantasette
      - ottantasette punto uno
      - ottantasette punto due
      - ottantasette punto tre
      - ottantasette punto quattro
      - ottantasette punto cinque
      - ottantasette punto sei
      - ottantasette punto sette
      - ottantasette punto otto
      - ottantasette punto nove
      - ottantotto
      - ottantotto punto uno
      - ottantotto punto due
      - ottantotto punto tre
      - ottantotto punto quattro
      - ottantotto punto cinque
      - ottantotto punto sei
      - ottantotto punto sette
      - ottantotto punto otto
      - ottantotto punto nove
      - ottantanove
      - ottantanove punto uno
      - ottantanove punto due
      - ottantanove punto tre
      - ottantanove punto quattro
      - ottantanove punto cinque
      - ottantanove punto sei
      - ottantanove punto sette
      - ottantanove punto otto
      - ottantanove punto nove
      - novanta
      - novanta punto uno
      - novanta punto due
      - novanta punto tre
      - novanta punto quattro
      - novanta punto cinque
      - novanta punto sei
      - novanta punto sette
      - novanta punto otto
      - novanta punto nove
      - novantuno
      - novantuno punto uno
      - novantuno punto due
      - novantuno punto tre
      - novantuno punto quattro
      - novantuno punto cinque
      - novantuno punto sei
      - novantuno punto sette
      - novantuno punto otto
      - novantuno punto nove
      - novantadue
      - novantadue punto uno
      - novantadue punto due
      - novantadue punto tre
      - novantadue punto quattro
      - novantadue punto cinque
      - novantadue punto sei
      - novantadue punto sette
      - novantadue punto otto
      - novantadue punto nove
      - novantatre
      - novantatre punto uno
      - novantatre punto due
      - novantatre punto tre
      - novantatre punto quattro
      - novantatre punto cinque
      - novantatre punto sei
      - novantatre punto sette
      - novantatre punto otto
      - novantatre punto nove
      - novantaquattro
      - novantaquattro punto uno
      - novantaquattro punto due
      - novantaquattro punto tre
      - novantaquattro punto quattro
      - novantaquattro punto cinque
      - novantaquattro punto sei
      - novantaquattro punto sette
      - novantaquattro punto otto
      - novantaquattro punto nove
      - novantacinque
      - novantacinque punto uno
      - novantacinque punto due
      - novantacinque punto tre
      - novantacinque punto quattro
      - novantacinque punto cinque
      - novantacinque punto sei
      - novantacinque punto sette
      - novantacinque punto otto
      - novantacinque punto nove
      - novantasei
      - novantasei punto uno
      - novantasei punto due
      - novantasei punto tre
      - novantasei punto quattro
      - novantasei punto cinque
      - novantasei punto sei
      - novantasei punto sette
      - novantasei punto otto
      - novantasei punto nove
      - novantasette
      - novantasette punto uno
      - novantasette punto due
      - novantasette punto tre
      - novantasette punto quattro
      - novantasette punto cinque
      - novantasette punto sei
      - novantasette punto sette
      - novantasette punto otto
      - novantasette punto nove
      - novantotto
      - novantotto punto uno
      - novantotto punto due
      - novantotto punto tre
      - novantotto punto quattro
      - novantotto punto cinque
      - novantotto punto sei
      - novantotto punto sette
      - novantotto punto otto
      - novantotto punto nove
      - novantanove
      - novantanove punto uno
      - novantanove punto due
      - novantanove punto tre
      - novantanove punto quattro
      - novantanove punto cinque
      - novantanove punto sei
      - novantanove punto sette
      - novantanove punto otto
      - novantanove punto nove
      - cento

```

* * *

$ cat data/intents.yml (excerpt)

```auto
nlu:
  - intent: body_temperature_data
    examples: |
      - sto bene
      - niente febbre
      - normale
      - sono senza febbre
      - non ho febbre
      - non mi sento la febbre
      - ho qualche linea
      - ho la febbre
      - credo di avere la febbre
      - mi sento un po di febbre
      - mi sento caldo
      - poca
      - molto poca
      - bassa
      - alta
      - molto alta
      - temperatura: [35](body_temperature) gradi
      - la temperatura è [ovantadue](oxygen_saturation) gradi
      - [35.5](body_temperature)
      - [35.9](body_temperature) gradi
      - [35 e 9](body_temperature)
      - [35,9](body_temperature)
      - [36](body_temperature) esatti
      - [36.0](body_temperature)
      - [36 e 7](body_temperature)
      - [36 , 8](body_temperature)
      - [36,9](body_temperature)
      - [37](body_temperature) gradi esatti
      - [37.9](body_temperature)
      - [37,2](body_temperature)
      - [37.5](body_temperature) gradi
      - [37 , 6](body_temperature)
      - [37 . 6](body_temperature)
      - [38 e 8](body_temperature)
      - [38 , 1](body_temperature)
      - [38 . 2](body_temperature)
      - [39 e 3](body_temperature) linee
      - [trentasei e otto](body_temperature) linee
      - la temperatura è [trentasette](body_temperature)
      - [trentasette emmezzo](body_temperature)
      - [trentasette e mezzo](body_temperature)
      - [trentasette punto otto](body_temperature)
      - [trentasette e quattro lineette](body_temperature)
      - [trentasette e 6](body_temperature) linee
      - [trentasette virgola sei](body_temperature)
      - ho [trentotto](body_temperature) di temperatura
      - ho [trentotto e 2](body_temperature) linee
      - [trentotto e due](body_temperature)
      - [trentotto virgola tre](body_temperature)
      - [trentotto e quattro](body_temperature)
      - [trentotto virgola quattro](body_temperature)
      - [trentotto emmezzo](body_temperature)
      - [trentanove e due](body_temperature)
      - [trentanove emmezzo](body_temperature)
      - [quaranta](body_temperature)
      - [quarantuno](body_temperature)

  - intent: oxygen_saturation_data
    examples: |
      - il valore è [70](oxygen_saturation)
      - ho [76 e 5](oxygen_saturation)
      - [77 e 9](oxygen_saturation)
      - [78,7](oxygen_saturation)
      - [95](oxygen_saturation)
      - [95.4](oxygen_saturation)
      - [96](oxygen_saturation)
      - [97](oxygen_saturation)
      - [97.5](oxygen_saturation)
      - esattamente [98](oxygen_saturation)
      - [98,4](oxygen_saturation)
      - [99 e mezzo](oxygen_saturation)
      - [99 e 1](oxygen_saturation)
      - [99](oxygen_saturation) preciso
      - [99.9](oxygen_saturation)
      - [100](oxygen_saturation)
      - circa [settantotto](oxygen_saturation)
      - quasi [settantanove](oxygen_saturation)
      - [ottanta](oxygen_saturation)
      - precisamentee [settantasette](oxygen_saturation)
      - [ottantatre emmezzo](oxygen_saturation)
      - [ottantatre virgola sei](oxygen_saturation)
      - [ottantaquattro emmezzo](oxygen_saturation)
      - [ottantaquattro e sei](oxygen_saturation)
      - [ottantaquattro virgola sette](oxygen_saturation)
      - [ottantaquattro virgola sei](oxygen_saturation)
      - [ottantaquattro e nove](oxygen_saturation)
      - [puntopuntiottantacinque](oxygen_saturation)
      - [ottantacinque punto cinque](oxygen_saturation)
      - [ottantacinque e quattro](oxygen_saturation)
      - proprio [ottantasei](oxygen_saturation)
      - il valore è [ottantasette](oxygen_saturation) preciso
      - [ottantotto](oxygen_saturation) tondi
      - giusto [ottantanove](oxygen_saturation)
      - [novanta](oxygen_saturation) giusto
      - [novanta e tre](oxygen_saturation)
      - [novanta virgola otto](oxygen_saturation)
      - [novantuno](oxygen_saturation)
      - [novantuno e nove](oxygen_saturation)
      - [novantadue](oxygen_saturation)
      - [novantadue emmezzo](oxygen_saturation)
      - [novantatre e sei](oxygen_saturation)
      - [novantatre virgola otto](oxygen_saturation)
      - [novantatre e due](oxygen_saturation)
      - [novantatre virgola nove](oxygen_saturation)
      - [novantaquattro](oxygen_saturation)
      - [novantaquattro punto due](oxygen_saturation)
      - [novantaquattro virgola otto](oxygen_saturation)
      - [novantacinque](oxygen_saturation)
      - [novantacinque e cinque](oxygen_saturation)
      - [novantacinque punto cinque](oxygen_saturation)
      - [novantasei](oxygen_saturation)
      - [novantasei e uno](oxygen_saturation)
      - [novantasei e cinque](oxygen_saturation)
      - [novantasette](oxygen_saturation)
      - [novantasette punto due](oxygen_saturation)
      - [novantasette e sei](oxygen_saturation)
      - [novantotto](oxygen_saturation)
      - [novantotto e cinque](oxygen_saturation)
      - [novantanove](oxygen_saturation)
      - [novantanove emmezzo](oxygen_saturation)
      - [cento](oxygen_saturation)

```

* * *

$ rasa shell nlu

```json
2021-08-15 18:01:31 INFO rasa.model - Loading model models/20210815-175244.tar.gz...
2021-08-15 18:01:36 INFO rasa.nlu.components - Added 'SpacyNLP' to component cache. Key 'SpacyNLP-it_core_news_sm'.
NLU model loaded. Type a message and press enter to parse it.
Next message:
90.3
{
  "text": "90.3",
  "intent": {
    "id": 7258451808749595588,
    "name": "oxygen_saturation_data",
    "confidence": 0.9954347610473633
  },
  "entities": [
    {
      "entity": "oxygen_saturation",
      "start": 0,
      "end": 4,
      "confidence_entity": 0.9767475724220276,
      "value": "90.3",
      "extractor": "DIETClassifier"
    }
  ],

Next message:
novnt virgola tri
{
  "text": "novnt virgola tri",
  "intent": {
    "id": 7258451808749595588,
    "name": "oxygen_saturation_data",
    "confidence": 0.9423763155937195
  },
  "entities": [
    {
      "entity": "oxygen_saturation",
      "start": 6,
      "end": 13,
      "confidence_entity": 0.8582544922828674,
      "value": "virgola",
      "extractor": "DIETClassifier"
    }
  ],

Next message:
ho trentasette gradi giusti
{
  "text": "ho trentasette gradi giusti",
  "intent": {
    "id": -3485198568115343109,
    "name": "body_temperature_data",
    "confidence": 0.9999998807907104
  },
  "entities": [
    {
      "entity": "body_temperature",
      "start": 3,
      "end": 14,
      "confidence_entity": 0.9392516613006592,
      "value": "trentasette",
      "extractor": "DIETClassifier"
    }
  ],

ho trentotto emmezzo di febbre
{
  "text": "ho trentotto emmezzo di febbre",
  "intent": {
    "id": -3485198568115343109,
    "name": "body_temperature_data",
    "confidence": 1.0
  },
  "entities": [
    {
      "entity": "body_temperature",
      "start": 3,
      "end": 20,
      "confidence_entity": 0.7569668889045715,
      "value": "trentotto emmezzo",
      "extractor": "DIETClassifier"
    }
  ],
Next message:
38 virgola cinque
{
  "text": "38 virgola cinque",
  "intent": {
    "id": -583108352491052127,
    "name": "body_temperature_data",
    "confidence": 0.9998660683631897
  },
  "entities": [
    {
      "entity": "body_temperature",
      "start": 0,
      "end": 17,
      "confidence_entity": 0.8543928861618042,
      "value": "38 virgola cinque",
      "extractor": "DIETClassifier"
    }
  ],
Next message:
la teperatura è di trentotto gradi esatti
{
  "text": "la teperatura è di trentotto gradi esatti",
  "intent": {
    "id": -583108352491052127,
    "name": "body_temperature_data",
    "confidence": 0.9999998807907104
  },
  "entities": [
    {
      "entity": "body_temperature",
      "start": 19,
      "end": 28,
      "confidence_entity": 0.978223979473114,
      "value": "trentotto",
      "extractor": "DIETClassifier"
    }
  ],
Next message:
temperatura: ternt'otto gradi emmezzo
{
  "text": "temperatura: ternt'otto gradi emmezzo",
  "intent": {
    "id": -583108352491052127,
    "name": "body_temperature_data",
    "confidence": 0.9999991059303284
  },
  "entities": [
    {
      "entity": "oxygen_saturation",
      "start": 30,
      "end": 37,
      "confidence_entity": 0.7737781405448914,
      "value": "emmezzo",
      "extractor": "DIETClassifier"
    }
  ],

```

See also the blog post: [10 Best Practices for Designing NLU Training Data](https://blog.rasa.com/10-best-practices-for-designing-nlu-training-data/)

* * *

---

<div class="post-metadata">

**Author:** ![nik202](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/nik202/32/16098_2.png) [@nik202](https://forum.rasa.com/u/nik202)\
**Post date:** [August 15, 2021, 6:58pm UTC](https://forum.rasa.com/t/wrong-intent-and-entity-detected-if-examples-contains-numbers-as-digit-sequences/46860/11 "2021-08-15T18:58:08Z")

</div>

@solyarisoftware congratulates 👏👏, Finally. Please close this thread with your solution, which you shared in last post and good luck with you project.