Triple
T20921135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sag Harbor Cinema Arts Center |
E515209
|
entity |
| Predicate | languageOfMostProgramming |
P141684
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Sag Harbor Cinema Arts Center, languageOfMostProgramming, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfMostProgramming Context triple: [Sag Harbor Cinema Arts Center, languageOfMostProgramming, English]
-
A.
languageOfPrimaryProgramming
Indicates the programming language that is primarily used to implement or develop a given entity.
-
B.
languageOfProgramming
Indicates that one entity is a programming language used to implement, develop, or script the other entity.
-
C.
primaryLanguageOfPrograms
Indicates that a given language is the main programming language used to implement or develop the specified programs.
-
D.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
E.
programmingLanguageUsage
Indicates that an entity uses, is implemented in, or otherwise employs a particular programming language.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f64e56bc81908aa86f2176fcc0db |
completed | April 21, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e5c9af1fe08190953366a466950140 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53d22d08190bc17ed4bed53804a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:48 p.m.