---
sourceDocument: Australia Conversational Interfaces
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/pt-BR/conversational-interfaces

 Release :

    - australia

ft:locale :

    - pt-BR

ft:publication_title :

    - Australia Conversational Interfaces

ft:clusterId :

    - convint

bundleId :

    - convint

workflow :

    - Platform


---

# NLU system entities

# NLU system entities {#ariaid-title1}

* Versão de lançamento: Australia
* 
* Atualizado 12 de mar. de 2026
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 5 min. de leitura

Use globally defined NLU entities to identify system
information that Virtual Agent can extract from the conversation. You can define
entities as "nodeless" input variables for a topic. These variables can be slot-filled from NLU service provider predictions or provided outside of the scope of the
topic.
System entities are enabled in NLU models by default. You can
view them on the model Entities tab in NLU Workbench.

## GLOBAL.DATE system entity {#nlu-system-entities__section_cqn_53d_lpb}

The DAY SubType returns a date string that is accurate to a specific date.  
{#nlu-system-entities__table_lcl_cjd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | YYYY-MM-DD |
| Regular expression | \\\\d\\\\d\\\\d\\\\d-\\\\d\\\\d-\\\\d\\\\d |
| Input example | Mr. Smith left Friday, February 4, 2019. |
| Normalized value | 2019-02-04 |
| Code example | { "name": "DATE", "value": "...", "score": 1.0, "normalization": "2019-02-04" } |
[Tabela 1. GLOBAL.DATE SubType = DAY usage]

{#nlu-system-entities__table_lcl_cjd_lpb}

The WEEK SubType returns a date string of a specific week of a year.  
{#nlu-system-entities__table_crg_tjd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | YYYY'W'WW |
| Regular expression | \\\\d\\\\d\\\\d\\\\d\\\\dW\\\\d\\\\d |
| Input example | Mr. Smith left the third week of 1999. |
| Normalized value | 1999W3 |
| Code example | { "name": "entity:GLOBAL.DATE", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.DATE", "subType": "WEEK", "value":"1999W3"} } |
[Tabela 2. GLOBAL.DATE SubType = WEEK usage]

{#nlu-system-entities__table_crg_tjd_lpb}

The MONTH SubType returns a date string of a specific month of a year.  
{#nlu-system-entities__table_edh_sld_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | YYYY'M'MM |
| Regular expression | \\\\d\\\\d\\\\d\\\\dM\\\\d\\\\d |
| Input example | Mr. Smith left in February of 1999. |
| Normalized value | 1999M02 |
| Code example | { "name": "entity:GLOBAL.DATE", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.DATE", "subType": "MONTH", "value": "1999M02"} } |
[Tabela 3. GLOBAL.DATE SubType = MONTH usage]

{#nlu-system-entities__table_edh_sld_lpb}

The YEAR SubType returns a date string of a specific year.  
{#nlu-system-entities__table_pxj_1md_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | YYYY |
| Regular expression | \\\\d\\\\d\\\\d\\\\d |
| Input example | Mr. Smith left in 1999. |
| Normalized value | 1999 |
| Code example | { "name": "entity:GLOBAL.DATE", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.DATE", "subType": "YEAR", "value": "1999"} } |
[Tabela 4. GLOBAL.DATE SubType = YEAR usage]

{#nlu-system-entities__table_pxj_1md_lpb}

The SEASON SubType returns a date string of a specific season of the year.  
{#nlu-system-entities__table_s1q_fpd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | One of the following: * Winter: YYYYWI * Spring: YYYYSP * Summer: YYYYSU * Fall: YYYYFA {#nlu-system-entities__ul_m4j_jpd_lpb} |
| Regular expression | One of the following: * Winter: \\\\d\\\\d\\\\d\\\\dWI * Spring: \\\\d\\\\d\\\\d\\\\dSP * Summer: \\\\d\\\\d\\\\d\\\\dSU * Fall: \\\\d\\\\d\\\\d\\\\dFA {#nlu-system-entities__ul_cnh_npd_lpb} |
| Input example | Mr. Smith left in the fall of 1999. |
| Normalized value | 1999FA |
| Code example | { "name": "entity:GLOBAL.DATE", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.DATE", "subType": "SEASON", "value": "1999FA"} } |
[Tabela 5. GLOBAL.DATE SubType = SEASON usage]

{#nlu-system-entities__table_s1q_fpd_lpb}

## GLOBAL.TIME system entity {#nlu-system-entities__section_rrk_kqd_lpb}

The TIME SubType returns a time string that is accurate to an hour and a minute.  
{#nlu-system-entities__table_zrm_mqd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | 'T'HH:mm |
| Regular expression | T\\\\d\\\\d:\\\\d\\\\d |
| Input example | Mr. Smith left at ten minutes to three. |
| Normalized value | T02:50 |
| Code example | { "name": "entity:GLOBAL.TIME", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.TIME","subType": "TIME", "value": "T02:50"} } |
[Tabela 6. GLOBAL.TIME SubType = TIME usage]

{#nlu-system-entities__table_zrm_mqd_lpb}

The PARTSOFDAY SubType returns a time string that specifies parts of the day.  
{#nlu-system-entities__table_thr_wqd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | One of the following: * Morning: TMO * Afternoon: TAF * Evening: TEV * Night: TNI {#nlu-system-entities__ul_xl5_crd_lpb} |
| Regular expression | One of the following: * Morning: TMO * Afternoon: TAF * Evening: TEV * Night: TNI {#nlu-system-entities__ul_omc_grd_lpb} |
| Input example | Mr. Smith left in the morning. |
| Normalized value | TMO |
| Code example | { "name": "entity:GLOBAL.TIME", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.TIME", "subType": "PARTSOFDAY", "value": "TMO"} } |
[Tabela 7. GLOBAL.TIME SubType = PARTSOFDAY usage]

{#nlu-system-entities__table_thr_wqd_lpb}

## GLOBAL.DATE_TIME system entity {#nlu-system-entities__section_rkt_pbc_3vb}

The DATE_TIME SubType returns a date string that is accurate to a specific date and time
string that is accurate to an hour and a minute.  
{#nlu-system-entities__table_wsh_ybc_3vb__entry__2}

| Usage | Example |
|-|-|
| Format | YYYY-MM-DD'T'HH:mm |
| Regular expression | \\\\d\\\\d\\\\d\\\\d-\\\\d\\\\d-\\\\d\\\\dT\\\\d\\\\d:\\\\d\\\\d |
| Input example | Mr. Smith leaves on October 31st at 5:00 p.m. |
| Normalized value | 2022-10-31T17:00 |
| Code example | { "name": "DATE_TIME", "value": "October 31st at 5:00 p.m", "normalization": "2022-10-31T17:00","confidence": "1" } |
[Tabela 8. GLOBAL.DATE_TIME SubType = DATETIME usage]

{#nlu-system-entities__table_wsh_ybc_3vb}

## GLOBAL.DURATION system entity {#nlu-system-entities__section_qhq_jrd_lpb}

This entity returns a duration string that specifies the duration of the activity.  
{#nlu-system-entities__table_gf3_mrd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | One of the following: * Second: 's'ss * Minute: 'm'mm * Hour: 'h'hh * Day: 'D'DD * Week: 'W'WW * Month: 'M'MM * Year: 'Y'YY {#nlu-system-entities__ul_dkp_qrd_lpb} |
| Regular expression | One of the following: * Second: s\\\\d\\\\d * Minute: m\\\\d\\\\d * Hour: h\\\\d\\\\d * Day: D\\\\d\\\\d * Week: W\\\\d\\\\d * Month: M\\\\d\\\\d * Year: Y\\\\d\\\\d {#nlu-system-entities__ul_bcb_yrd_lpb} |
| Input example | Mr. Smith stayed in Boston for 48 hours. |
| Normalized value | h48 |
| Code example | { "name": "entity:GLOBAL.DURATION", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.DURATION", "value": "h48"} } |
[Tabela 9. GLOBAL.DURATION usage]

{#nlu-system-entities__table_gf3_mrd_lpb}

## GLOBAL.LOCATION system entity {#nlu-system-entities__section_wpj_2sd_lpb}

This entity returns a location string.  
{#nlu-system-entities__table_wd5_cvd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | String value. Example: Santa Clara |
| Regular expression | Not applicable. |
| Input example | Mr. Smith works in Santa Clara. |
| Normalized value | Santa Clara |
| Code example | { "name": "entity:GLOBAL.LOCATION", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.LOCATION", "value":"Santa Clara"} } |
[Tabela 10. GLOBAL.LOCATION usage]

{#nlu-system-entities__table_wd5_cvd_lpb}

## GLOBAL.PERSON system entity {#nlu-system-entities__section_b1x_jvd_lpb}

This entity returns a name string.  
{#nlu-system-entities__table_og1_nvd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | String value. Example: Joe Smith |
| Regular expression | Not applicable. |
| Input example | Joe Smith works in Santa Clara. |
| Normalized value | Joe Smith |
| Code example | { "name": "entity:GLOBAL.PERSON", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.PERSON", "value":"Joe Smith"} } |
[ ]

{#nlu-system-entities__table_og1_nvd_lpb}

## GLOBAL.MONEY system entity {#nlu-system-entities__section_xkc_5vd_lpb}

This entity returns a currency string.  
{#nlu-system-entities__table_c1b_wvd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | String value. Example: USD 2000 |
| Regular expression | Not applicable. |
| Input example | Show me laptops for less than $2000. |
| Normalized value | USD 2000 Nota: The normalized value uses the three-letter ISO 3166 country code of the source currency. |
| Code example | { "name": "entity:GLOBAL.MONEY", "value": "...", "score": 1.0, "normalization": {"type": "GLOBAL.MONEY", "value":"2000", "currency":"USD"} } |
[Tabela 11. GLOBAL.MONEY usage]

{#nlu-system-entities__table_c1b_wvd_lpb}

## GLOBAL.NUMBER system entity {#nlu-system-entities__section_fn2_ywd_lpb}

This entity returns a number.  
{#nlu-system-entities__table_jxp_byd_lpb__entry__2}

| Usage | Example |
|-|-|
| Format | String value. Example: 5.0 |
| Regular expression | Not applicable. |
| Input example | I want to see the previous 5 transactions from my account. |
| Normalized value | 5.0 |
| Code example | { "name": "entity:GLOBAL.NUMBER", "value": "...", "score": 1.0, "normalization": {"numericValue":"5", "normalizedValue": "5"} } |
[ ]

{#nlu-system-entities__table_jxp_byd_lpb}

## GLOBAL.SOFTWARE {#nlu-system-entities__section_cr2_scy_brb}

Returns a software string.  
{#nlu-system-entities__table_oq4_vcy_brb__entry__2}

| Usage | Example |
|-|-|
| Format | String value. Example: Java |
| Regular expression | Not applicable. |
| Input example | How do I install Java? |
| Normalized value | Java |
| Code example | { "name": "entity:GLOBAL.SOFTWARE", "value": "Java", "score": 0.99930537, "normalization": {"type":"entity:GLOBAL.SOFTWARE", "subType":"SOFTWARE", "value":"Java"} } |
[ ]

{#nlu-system-entities__table_oq4_vcy_brb}

## GLOBAL.HARDWARE {#nlu-system-entities__section_bdt_xcy_brb}

Returns a hardware string.  
{#nlu-system-entities__table_dfl_ycy_brb__entry__2}

| Usage | Example |
|-|-|
| Format | String value. Example: printer |
| Regular expression | Not applicable. |
| Input example | How do I order a printer? |
| Normalized value | printer |
| Code example | { "name": "entity:GLOBAL.HARDWARE", "value": "printer", "score": 1.0, "normalization": {"type":"entity:GLOBAL.HARDWARE", "subType":"HARDWARE", "value":"printer"} } |
[ ]

{#nlu-system-entities__table_dfl_ycy_brb}

## Example NLU prediction result using Software system
entity {#nlu-system-entities__section_hlp_xdy_brb}

    {"status":"success",
       "response":{
          "utterance":"How do I install Java?",
          "intents":[
             {
                "intentName":"test intent",
                "nluModelName":"ml_x_snc_global_global_268a97a9dbd23c107906265d1396191a",
                "score":0.90401393,
                "intents":[
                   
                ],
                "entities":[
                   {
                      "name":"entity:GLOBAL.SOFTWARE",
                      "value":"Java",
                      "score":0.99930537,
                      "normalization":{
                         "type":"entity:GLOBAL.SOFTWARE",
                         "subType":"SOFTWARE",
                         "value":"Java"
                      },
                      "startingPosition":-1
                   }
                ]
             }
          ],
          "properties":{
             "all:ml_x_snc_global_global_268a97a9dbd23c107906265d1396191a":"0.55",
             "entity:all":"0.01",
             "inference.sspace.time":"4",
             "inference.time":"33",
             "intent:all":"0.01",
             "nluPlatformLanguage":"en",
             "nluPlatformVersion":"rome.0"
          }
       }
    }

## Example NLU prediction result using DATE system
entity {#nlu-system-entities__section_f4c_gxd_lpb}

    {
        "utterance": "We should meet next Sunday at Starbucks.",
        "intents": [
            {
                "intentName": "intent:Desire.Desire",
                "score": 0.83452,
                "entities": []
            },
            {
                "intentName": "intent:Meeting.MeetRequest",
                "score": 0.8919042,
                "entities": [
                    {
                        "entityName": "entity:Meeting.MeetRequest.Where",
                        "value": "Starbucks",
                        "score": 1
                    },
         {
                        "entityName": "entity:GLOBAL.DATE",
                        "value": "Sunday",
                        "normalization": { "type": "DATE",
                            "subType": "DAY",
                            "value": "1999-10-01"
                         },
                        "score": 0.87
                    }
                ]
            }
        ]
    }

**Conceitos relacionados**   

* [Domain separation and Virtual Agent](https://servicenow-prod.fluidtopics.net/p97iDOKngkoO5SaBoHj7xg "Domain separation is supported in the Virtual Agent application. Domain separation enables you to separate data, processes, and administrative tasks into logical groupings called domains. You can control several aspects of this separation, including which users can see and access data.")
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* [Latency feedback in Virtual Agent](https://servicenow-prod.fluidtopics.net/3VJeL1GYhJk1zOJhcr3VlQ "The com.glide.cs.message.processing.enabled system property notifies requesters whenever the generative AI large language model (LLM) is processing their request in the Virtual Agent chat widget and Now Assist panel.")