Triple
T32070230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Déjà Vu (1985 film) |
E818988
|
entity |
| Predicate | originatingIndustry |
P158848
|
FINISHED |
| Object | British film industry |
—
|
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: British film industry | Statement: [Déjà Vu (1985 film), originatingIndustry, British film industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originatingIndustry Context triple: [Déjà Vu (1985 film), originatingIndustry, British film industry]
-
A.
foundingIndustry
Indicates the industry or sector in which an entity was originally founded or began its primary operations.
-
B.
industryOfOrigin
chosen
Indicates the industry or sector from which an entity (such as a company, product, or person) originally comes or was first established.
-
C.
industryStart
Indicates the point in time or event at which an industry, industrial activity, or industrial era begins.
-
D.
operatorIndustry
Indicates that an operator (such as a company or organization) is engaged in or associated with a particular industry sector.
-
E.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a015ff02814819094806517fc4c69fa |
completed | May 11, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_6a0154ddd3c48190b85f9f48731cfd8f |
completed | May 11, 2026, 4:02 a.m. |
Created at: May 1, 2026, 12:23 a.m.