Triple
T37090176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Supporting Actor for Manchester by the Sea |
E918391
|
entity |
| Predicate | forGenre |
P82410
|
FINISHED |
| Object | drama film |
—
|
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: drama film | Statement: [Academy Award for Best Supporting Actor for Manchester by the Sea, forGenre, drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: forGenre Context triple: [Academy Award for Best Supporting Actor for Manchester by the Sea, forGenre, drama film]
-
A.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
B.
targetGenre
chosen
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
C.
favoriteGenre
Indicates that one entity’s preferred or most liked genre, among several possible genres, is the other entity.
-
D.
fandomGenre
Indicates that something belongs to, is associated with, or is categorized under a particular fandom-related genre.
-
E.
namedForGenre
Indicates that something is given a name based on or derived from a particular genre.
- 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_69f76e9952b88190a6fe01ba01476520 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.