Triple
T18709064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Call Me by Your Name |
E457449
|
entity |
| Predicate | lgbtCinema |
P45364
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Call Me by Your Name, lgbtCinema, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lgbtCinema Context triple: [Call Me by Your Name, lgbtCinema, yes]
-
A.
filmSelection
Indicates the act or result of choosing a particular film from a set of available options.
-
B.
cultFilm
Indicates that a film has acquired a dedicated, passionate fan following, often despite limited mainstream success or initial popularity.
-
C.
cinemaCategory
Indicates the classification or genre category assigned to a cinema or film.
-
D.
cinemaOf
Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
-
E.
hasLGBTTheme
chosen
Indicates that the subject includes, features, or centrally involves lesbian, gay, bisexual, or transgender themes or issues.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56719383481909d68c9e873ca0800 |
completed | April 19, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:50 a.m.