Triple
T27961044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glamour of Hollywood |
E704575
|
entity |
| Predicate | industryDepicted |
P102466
|
FINISHED |
| Object | 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: film industry | Statement: [Glamour of Hollywood, industryDepicted, film industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industryDepicted Context triple: [Glamour of Hollywood, industryDepicted, film industry]
-
A.
targetIndustryDepicted
chosen
Indicates that an entity visually represents or portrays a specific industry as its primary subject or focus.
-
B.
industryContext
Indicates the industry or sector within which an entity, activity, or relationship is situated or most relevant.
-
C.
industryActivities
Indicates the types of economic or business activities in which an industry or sector is engaged.
-
D.
industryStart
Indicates the point in time or event at which an industry, industrial activity, or industrial era begins.
-
E.
industryIntegrated
Indicates that something is closely connected or coordinated with industry practices, partners, or environments, often through collaboration, alignment, or direct involvement.
- 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_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 7:31 p.m.