Triple
T1227565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinderella Man |
E26359
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Mike Hill |
E102705
|
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: Mike Hill | Statement: [Cinderella Man, editedBy, Mike Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Hill Context triple: [Cinderella Man, editedBy, Mike Hill]
-
A.
Mike Hill
chosen
Mike Hill was an American film editor best known for his long-time collaboration with director Ron Howard on acclaimed films such as "A Beautiful Mind."
-
B.
Kevin Hageman
Kevin Hageman is an American screenwriter and producer known for his work on animated and family films and television series, including contributions to The Lego Movie franchise.
-
C.
Phil Smith
Phil Smith was an American professional basketball player best known as a two-time NBA All-Star guard and key contributor to the Golden State Warriors’ 1975 championship team.
-
D.
Michael Barrett
Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
-
E.
Kevin Chapman
Kevin Chapman is an American actor known for his tough, blue-collar character roles in film and television, including prominent parts in series like "Person of Interest" and "City on a Hill."
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be3b32a08190a36e96a3e51976eb |
completed | March 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1a06d7c8190b6c38ff6d18a4542 |
completed | March 8, 2026, 7:44 p.m. |
Created at: March 1, 2026, 7:47 p.m.