Triple
T2436650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mervyn LeRoy |
E52975
|
entity |
| Predicate | hasHollywoodWalkOfFameStar |
P39315
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mervyn LeRoy, hasHollywoodWalkOfFameStar, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHollywoodWalkOfFameStar Context triple: [Mervyn LeRoy, hasHollywoodWalkOfFameStar, true]
-
A.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
B.
notableStar
Indicates that the subject is a star (or stellar object) that is distinguished or noteworthy in some significant way, such as brightness, fame, or scientific interest, relative to other stars.
-
C.
hasNotableHonoree
Indicates that an entity is notably dedicated to, named after, or honors a particular person or group.
-
D.
academyAwardWins
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.
-
E.
wasProminentIn
Indicates that an entity was notably active, influential, or widely recognized within a particular field, context, or time period.
- F. None of above. chosen
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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
| PDg | Predicate description generation | batch_69abcebe7dd08190b197a2a0e78787e3 |
completed | March 7, 2026, 7:07 a.m. |
Created at: March 6, 2026, 9:43 p.m.