Triple
T6954875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pain & Gain |
E161216
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Ed Harris |
E29208
|
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: Ed Harris | Statement: [Pain & Gain, starring, Ed Harris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ed Harris Context triple: [Pain & Gain, starring, Ed Harris]
-
A.
Ed Harris
chosen
Ed Harris is an American actor and filmmaker known for his intense, authoritative performances in films such as "The Truman Show," "Apollo 13," and "Pollock."
-
B.
Michael York
Michael York is an English actor known for his roles in films such as "Cabaret," "Logan's Run," and the "Austin Powers" series.
-
C.
Danny Huston
Danny Huston is an American actor and director known for his character roles in films such as "The Constant Gardener," "X-Men Origins: Wolverine," and "Wonder Woman."
-
D.
George Norton
George Norton was a British colonial-era lawyer and educator best known for establishing Presidency College in Madras, one of India’s earliest and most prestigious institutions of higher learning.
-
E.
David Strathairn
David Strathairn is an American character actor known for his nuanced performances in film, television, and theater, including acclaimed roles in works like "Good Night, and Good Luck" and "Nomadland."
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dace1a94819095311e4288f01784 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e50580c08190aa737043ad7520a0 |
completed | March 28, 2026, 2:26 p.m. |
Created at: March 27, 2026, 2:29 p.m.