Triple
T23987727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Third Cinema |
E604982
|
entity |
| Predicate | definesFirstCinemaAs |
P154522
|
FINISHED |
| Object | commercial Hollywood cinema |
—
|
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: commercial Hollywood cinema | Statement: [Third Cinema, definesFirstCinemaAs, commercial Hollywood cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesFirstCinemaAs Context triple: [Third Cinema, definesFirstCinemaAs, commercial Hollywood cinema]
-
A.
primaryCinema
Indicates that one entity is the main or most significant cinema associated with another entity (such as a person, work, or event).
-
B.
cinemaOf
Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
-
C.
cinemaCategory
Indicates the classification or genre category assigned to a cinema or film.
-
D.
firstFilmScreenings
Indicates that the relationship links a film to the locations, venues, or events where it was first publicly screened.
-
E.
intendedTheater
Indicates the theater or venue that an event, performance, or screening is planned or meant to take place in.
- F. None of above. chosen
Provenance (4 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38838f481909a52fccd392a92df |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:36 p.m.