Triple
T1432837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Beach |
E30488
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Beach |
E30488
|
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: Michael Beach | Statement: [Michael Beach, name, Michael Beach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Beach Context triple: [Michael Beach, name, Michael Beach]
-
A.
Michael Beach
chosen
Michael Beach is an American actor known for his versatile supporting roles in film and television, including prominent appearances in dramas throughout the 1990s and 2000s.
-
B.
Stephen Dorff
Stephen Dorff is an American actor known for his intense performances in films such as "Blade," "Somewhere," and numerous independent and genre movies.
-
C.
Joshua Jackson
Joshua Jackson is a Canadian actor best known for his roles in the television series "Dawson's Creek," "Fringe," and "The Affair."
-
D.
Dermot Mulroney
Dermot Mulroney is an American actor known for his versatile film and television roles, including prominent performances in romantic comedies and dramas since the late 1980s.
-
E.
David Morse
David Morse is an American character actor known for his tall, imposing presence and roles in films such as The Green Mile, The Hurt Locker, and television series like St. Elsewhere.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c4ddbe208190a68cb000a6970d17 |
completed | March 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08b5ba94819092e66e8dfd6bf87d |
completed | March 8, 2026, 5:27 a.m. |
Created at: March 1, 2026, 8 p.m.