Triple
T18600853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Hegedus |
E454614
|
entity |
| Predicate | hasSubjectInFilms |
P22751
|
FINISHED |
| Object | politics |
—
|
LITERAL 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: politics | Statement: [Chris Hegedus, hasSubjectInFilms, politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectInFilms Context triple: [Chris Hegedus, hasSubjectInFilms, politics]
-
A.
subjectOfFilm
chosen
Indicates that a person, character, or topic is the main focus or central topic depicted in a particular film.
-
B.
hasFilmographyType
Indicates the type or category of film-related work associated with an entity (e.g., actor, director, producer) within its filmography.
-
C.
hasWorkedOnFilmBy
Indicates that one entity has worked on a film that was created, directed, or otherwise authored by another entity.
-
D.
followsInFilmography
Indicates that one work in a person’s filmography comes after another in chronological or credited order.
-
E.
partOfFilmographyOf
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.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5475112608190acacc5ac7a08c4a0 |
completed | April 19, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:45 a.m.