Triple
T37779506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian Argentines |
E941787
|
entity |
| Predicate | notableSettlementCountryOutsideEurope |
P41930
|
FINISHED |
| Object | Argentina |
E5383
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Argentina | Statement: [Austrian Argentines, notableSettlementCountryOutsideEurope, Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSettlementCountryOutsideEurope Context triple: [Austrian Argentines, notableSettlementCountryOutsideEurope, Argentina]
-
A.
notableSettlementCountry
chosen
Indicates that a country is notably associated with a particular settlement, such as being its primary or most recognized national affiliation.
-
B.
notableHumanSettlement
Indicates that a location is recognized as a significant or noteworthy human settlement, such as a city, town, or village.
-
C.
notableCountry
Indicates that a country holds particular significance or prominence in relation to the subject entity.
-
D.
notableProjectCountry
Indicates that a country is associated with a notable project undertaken by the subject.
-
E.
countryWithPrimaryInterest
Indicates that a specified country has the main or dominant interest, concern, or stake in a particular entity, issue, or context.
- F. None of above.
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76ee4431881908f87e8892a9f39f3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40fb6e3c2881908db9edda4835c74e |
completed | June 28, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.