Triple
T11995282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobey Maguire |
E285512
|
entity |
| Predicate | coStarredWith |
P14987
|
FINISHED |
| Object | Jeff Bridges |
E101127
|
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: Jeff Bridges | Statement: [Tobey Maguire, coStarredWith, Jeff Bridges]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Bridges Context triple: [Tobey Maguire, coStarredWith, Jeff Bridges]
-
A.
Jeff Bridges
chosen
Jeff Bridges is an acclaimed American actor known for his versatile performances in films such as "The Big Lebowski," "Crazy Heart," and "True Grit."
-
B.
Gene Hackman
Gene Hackman is an acclaimed American actor known for his powerful, versatile performances in films such as "The French Connection," "The Conversation," and "Unforgiven."
-
C.
Bill Paxton
Bill Paxton was an American actor and filmmaker known for his versatile roles in films such as "Aliens," "Twister," "Titanic," and "Apollo 13."
-
D.
Ned Beatty
Ned Beatty was an acclaimed American character actor known for his powerful supporting roles in films such as "Deliverance," "Network," and "Superman."
-
E.
Eric S. Roberts
Eric S. Roberts is a prominent computer scientist and educator known for his influential work in computer science pedagogy, curriculum development, and widely used textbooks.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f640b9a481908de1b7858e3db52c |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:46 p.m.