Triple
T22751825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Brackett |
E562720
|
entity |
| Predicate | engagementStatusAtStartOfFilm |
P131402
|
FINISHED |
| Object | engaged |
—
|
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: engaged | Statement: [Howard Brackett, engagementStatusAtStartOfFilm, engaged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagementStatusAtStartOfFilm Context triple: [Howard Brackett, engagementStatusAtStartOfFilm, engaged]
-
A.
engagementStatusAcrossFilm
Indicates the state or progression of an engagement (such as a relationship, commitment, or involvement) as it changes or is maintained throughout the duration of a film.
-
B.
statusAtStartOfFilm
chosen
Indicates the condition or situation an entity is in at the beginning of the film.
-
C.
statusDuringFilm
Indicates that a particular status or condition holds for an entity during the time span in which a specified film takes place or is being made.
-
D.
legalStatusAtStartOfFilm
Indicates the legal condition or standing an entity has at the beginning of the film’s narrative.
-
E.
statusAtEndOfFilm
Indicates the condition or situation an entity is in when the film concludes.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b9ac348190bff4dc470931f7e3 |
completed | April 29, 2026, 3:23 a.m. |
| PD | Predicate disambiguation | batch_69eed2b88d88819096015deb6a648801 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:24 p.m.