Triple
T2142823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toy Story 3 |
E46998
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Bullseye |
E237530
|
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: Bullseye | Statement: [Toy Story 3, mainCharacter, Bullseye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bullseye Context triple: [Toy Story 3, mainCharacter, Bullseye]
-
A.
Bullseye
Bullseye is a British television game show that combines darts with general knowledge quizzes, originally popular in the 1980s and 1990s.
-
B.
Bullseye
chosen
Bullseye is Woody’s loyal toy horse in the Toy Story franchise, known for his expressive, nonverbal personality and close bond with the other toys.
-
C.
Hardest Shot
Hardest Shot is a National Hockey League All-Star skills competition event in which players compete to record the fastest slap shot.
-
D.
Wild Target
Wild Target is a 2010 British black comedy film about an aging hitman whose life is upended when he protects a quirky young woman, featuring Emily Blunt in a leading role.
-
E.
Horseshoe
Horseshoe is a well-known casino and racetrack brand in the United States, recognized for its gambling, entertainment, and hospitality offerings.
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe206db0819095772af5358dca55 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58d5535c8190b59293afe3a10834 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:44 p.m.