Triple
T35142361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eric Stonestreet |
E1014726
|
entity |
| Predicate | hasFilmRoleIn |
P74071
|
FINISHED |
| Object | Bad Teacher |
—
|
NE NERFINISHED |
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: Bad Teacher | Statement: [Eric Stonestreet, hasFilmRoleIn, Bad Teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmRoleIn Context triple: [Eric Stonestreet, hasFilmRoleIn, Bad Teacher]
-
A.
hasFilmographyIn
Indicates that an individual has participated in or contributed to works within a specified filmography or body of film-related productions.
-
B.
hasFilmographyType
Indicates the type or category of film-related work associated with an entity (e.g., actor, director, producer) within its filmography.
-
C.
actsIn
chosen
Indicates that an entity performs or appears in a creative work, such as a film, play, or show.
-
D.
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.
-
E.
hasPortrayedRole
Indicates that an entity has performed or depicted a specific role or character, typically in a work such as a film, play, or television show.
- F. None of above.
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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffbe9e47688190a2692566dc326646 |
completed | May 9, 2026, 11:09 p.m. |
| PD | Predicate disambiguation | batch_69ffbb7b45388190b62cbde5c2d435cd |
completed | May 9, 2026, 10:55 p.m. |
Created at: May 3, 2026, 4:02 p.m.