Triple
T5118903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Gayton |
E115408
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Joe Gayton |
E187164
|
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: Joe Gayton | Statement: [Tony Gayton, collaboratedWith, Joe Gayton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Gayton Context triple: [Tony Gayton, collaboratedWith, Joe Gayton]
-
A.
Joe Gayton
chosen
Joe Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
-
B.
Tony Puryear
Tony Puryear is an American screenwriter best known for co-writing the 1996 action film "Eraser" starring Arnold Schwarzenegger.
-
C.
Glen Graham
Glen Graham is an American rock drummer best known as the percussionist for the alternative rock band Blind Melon.
-
D.
Mike Grier
Mike Grier is a former NHL winger who became the first Black general manager in league history when he took over hockey operations for the San Jose Sharks.
-
E.
Kevin Gage
Kevin Gage is an American actor best known for his intense supporting roles in films such as "Heat" and "G.I. Jane."
- 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_69bd4442ade0819087b9461f892b206b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd77cf6590819081488b739efae32c |
completed | March 20, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed9185b9481908afd32bdeefa3f1e |
completed | March 21, 2026, 5:44 p.m. |
Created at: March 20, 2026, 1:42 p.m.