Triple
T5008895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Close Encounters of the Third Kind film score |
E112564
|
entity |
| Predicate | associatedFilmGenre |
P9709
|
FINISHED |
| Object | science fiction |
—
|
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: science fiction | Statement: [Close Encounters of the Third Kind film score, associatedFilmGenre, science fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFilmGenre Context triple: [Close Encounters of the Third Kind film score, associatedFilmGenre, science fiction]
-
A.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
B.
genreOfWorkActedIn
Indicates that an entity is the genre category of a work in which another entity performed or acted.
-
C.
producedFilmType
Indicates that an entity (such as a person or organization) was responsible for producing a film of a specified type or category.
-
D.
genreOfWorkDirected
Indicates that a person has directed a work (such as a film, show, or performance) belonging to a specified genre.
-
E.
filmType
chosen
Indicates the specific category or genre that a film belongs to.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.