Triple
T8337347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruth Elizabeth Davis |
E195820
|
entity |
| Predicate | numberOfAcademyAwardWins |
P25589
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Ruth Elizabeth Davis, numberOfAcademyAwardWins, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAcademyAwardWins Context triple: [Ruth Elizabeth Davis, numberOfAcademyAwardWins, 2]
-
A.
academyAwardWins
chosen
Indicates that one entity has won a specified number of Academy Awards (Oscars) or that a winning relationship exists between the entity and the Academy Award.
-
B.
numberOfAcademyAwardsForBestActress
Indicates the total count of Academy Awards received by an entity specifically in the Best Actress category.
-
C.
academyAwardsNominationsCount
Indicates the number of times an entity has been nominated for an Academy Award.
-
D.
numberOfAcademyAwardsForBestDirector
Indicates the total count of Academy Awards received by a director for the Best Director category.
-
E.
numberOfEmmyNominations
Indicates the total count of Emmy Award nominations received by an entity.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd5027c81909724f25aa30bbe58 |
completed | March 31, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:57 p.m.