Triple
T11144865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy Feet Two |
E263643
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Bill Miller |
E901271
|
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: Bill Miller | Statement: [Happy Feet Two, producer, Bill Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Miller Context triple: [Happy Feet Two, producer, Bill Miller]
-
A.
Bill Miller
Bill Miller is a veteran Major League Baseball umpire who has officiated numerous high-profile games, including multiple World Series.
-
B.
Bill Miller
chosen
Bill Miller is a film producer best known for his work on the Academy Award–winning animated feature "Happy Feet."
-
C.
William F. Miller
William F. Miller was a prominent American physicist, academic leader, and technology executive known for his contributions to innovation management and university–industry collaboration.
-
D.
Bill Gross
Bill Gross is an American entrepreneur and investor best known for founding numerous technology companies and the startup incubator Idealab.
-
E.
Stuart Schwab
Stuart Schwab is an American legal scholar and former dean of Cornell Law School known for his work in employment law and economic analysis of law.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8634d5481909b114d30a542ea3f |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4421d35f48190a5905fbab39f4015 |
completed | April 19, 2026, 2:46 a.m. |
Created at: April 8, 2026, 9:28 p.m.