Triple
T9763941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thai American |
E236735
|
entity |
| Predicate | hasNotableFieldOfContribution |
P11898
|
FINISHED |
| Object | entertainment |
—
|
LITERAL 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: entertainment | Statement: [Thai American, hasNotableFieldOfContribution, entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFieldOfContribution Context triple: [Thai American, hasNotableFieldOfContribution, entertainment]
-
A.
notableContributionField
chosen
Indicates the field or domain in which an entity has made a significant or noteworthy contribution.
-
B.
notableContribution
Indicates that an entity has made a significant, recognized contribution to another entity, field, work, or endeavor.
-
C.
hasNotableProfessionField
Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
-
D.
hasNotableWorkCategory
Indicates that an entity’s notable work belongs to, or is classified under, a particular category or type.
-
E.
hasNotableCredit
Indicates that an entity is recognized for having a significant or noteworthy contribution, role, or acknowledgment associated with it.
- F. None of above.
Provenance (3 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_69ca84d64f6c8190a4ed4e9f5936eda5 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda09ed54c8190a5879e14184cddf4 |
completed | April 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69cd03d0772c8190bd1750cf1cfba309 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:25 p.m.