Triple
T2151903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toy Story 4 |
E47798
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Woody |
E62654
|
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: Woody | Statement: [Toy Story 4, mainCharacter, Woody]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woody Context triple: [Toy Story 4, mainCharacter, Woody]
-
A.
Woody
Woody is the commonly used nickname of American businessman and New York Jets owner Woody Johnson.
-
B.
Woody
Woody is the nickname of Woody Guthrie, the influential American folk singer-songwriter known for his protest music and the anthem "This Land Is Your Land."
-
C.
Woody in Toy Story
chosen
Woody in Toy Story is the loyal, cowboy doll leader of Andy’s toys and the central protagonist of Pixar’s Toy Story film series.
-
D.
Dug
Dug is the lovable, talking golden retriever from Pixar's animated film "Up," known for his collar that translates his thoughts into speech and his enthusiastic, friendly personality.
-
E.
Teddy
Teddy is Mr. Bean’s beloved brown teddy bear, a silent yet expressive companion that often serves as his confidant and playmate in the comedy series.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe48ad148190a7d6cc88fd38a660 |
completed | March 7, 2026, 5:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae653677ec8190ab0b044e005a9947 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:44 p.m.