Triple
T7802362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beauty and the Beast (musical) |
E180460
|
entity |
| Predicate | choreographer |
P11856
|
FINISHED |
| Object | Matt West |
E695606
|
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: Matt West | Statement: [Beauty and the Beast (musical), choreographer, Matt West]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt West Context triple: [Beauty and the Beast (musical), choreographer, Matt West]
-
A.
Matt West
chosen
Matt West is an American choreographer and actor best known for staging the original Broadway production of Disney’s "Beauty and the Beast."
-
B.
Robb Wells
Robb Wells is a Canadian actor and screenwriter best known for his role as Ricky on the mockumentary television series "Trailer Park Boys."
-
C.
Rick Wills
Rick Wills is an English rock bassist best known for his work with bands such as Foreigner, Small Faces, and Bad Company.
-
D.
Matt Ross
Matt Ross is an American actor and filmmaker known for roles in projects like "Big Love" and for directing the acclaimed film "Captain Fantastic."
-
E.
Michael West
Michael West is an entrepreneur best known as the founder of Pixelworks, a company specializing in advanced video and display processing technologies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae988bc2081909870bae1c2e9c238 |
completed | March 30, 2026, 9:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5a2fd718819097cee2482bca74ad |
completed | March 31, 2026, 5:22 a.m. |
Created at: March 30, 2026, 4:33 p.m.