Triple
T9873140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cars (video game) |
E240005
|
entity |
| Predicate | playableCharacter |
P43877
|
FINISHED |
| Object | Doc Hudson |
E236508
|
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: Doc Hudson | Statement: [Cars (video game), playableCharacter, Doc Hudson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doc Hudson Context triple: [Cars (video game), playableCharacter, Doc Hudson]
-
A.
Doc Hudson
chosen
Doc Hudson is a wise, retired race car and town doctor in Pixar's "Cars" who mentors the protagonist Lightning McQueen.
-
B.
Freddy Reynolds
Freddy Reynolds is an actor known for his role in the acclaimed Australian film "The Chant of Jimmie Blacksmith."
-
C.
Jack Binder
Jack Binder is a film producer known for his work on independent and studio features, including the critically acclaimed drama "First Reformed."
-
D.
Lester Freamon
Lester Freamon is a meticulous, soft-spoken detective in the TV series "The Wire," renowned for his patience, investigative brilliance, and skill at unraveling complex financial and wiretap cases.
-
E.
Holden
Holden is a small town in central Utah, United States, known for its rural character and proximity to Interstate 15.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f754008190abe3fe034b42908e |
completed | April 2, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20d60b2f8819087f4242f36b05a49 |
completed | April 5, 2026, 7:21 a.m. |
Created at: March 30, 2026, 8:37 p.m.