Triple
T38117302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Heckling Hare |
E951825
|
entity |
| Predicate | partOfCharacterFilmographyOf |
P15620
|
FINISHED |
| Object | Bugs Bunny |
E55364
|
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: Bugs Bunny | Statement: [The Heckling Hare, partOfCharacterFilmographyOf, Bugs Bunny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfCharacterFilmographyOf Context triple: [The Heckling Hare, partOfCharacterFilmographyOf, Bugs Bunny]
-
A.
partOfFilmographyOf
chosen
Indicates that a work (such as a film, show, or role) is included in the body of screen-related works credited to a particular person.
-
B.
filmCharacterOf
Indicates that a person or character is a character appearing in a specified film.
-
C.
featuredInFilmBy
Indicates that an entity is prominently included or showcased within a film that is created, directed, or produced by a specified person or organization.
-
D.
characterAppearsIn
Indicates that a specific character is present or featured within a particular work, such as a book, movie, or episode.
-
E.
sharesFilmWithCharacter
Indicates that one character appears in or is associated with at least one film that another specified character also appears in.
- F. None of above.
Provenance (4 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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a01a9e333fc819087d583ff319be0b3 |
completed | May 11, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4193b5c12c8190a4218377bf394945 |
completed | June 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_6a01a877c9e08190b0678618d3533286 |
completed | May 11, 2026, 9:59 a.m. |
Created at: May 3, 2026, 4:21 p.m.