Triple
T2720325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Film Company |
E60065
|
entity |
| Predicate | impactOnMarket |
P41849
|
FINISHED |
| Object | consolidation of film exchanges |
—
|
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: consolidation of film exchanges | Statement: [General Film Company, impactOnMarket, consolidation of film exchanges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnMarket Context triple: [General Film Company, impactOnMarket, consolidation of film exchanges]
-
A.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
B.
market
Indicates the act of promoting, advertising, or selling a product, service, or idea to potential buyers or target audiences.
-
C.
marketModel
Indicates the specific economic or pricing framework under which transactions or interactions in a market are structured and governed.
-
D.
impactIfCompleted
Indicates the effect or consequence that will occur if the referenced task or action is fully completed.
-
E.
impactOnLaw
Indicates the effect or influence that one entity, event, or action has on laws, legal rules, or the legal system.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdab06d388190acf690787fe58ab5 |
completed | March 7, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69abd8240920819087a812d816a55edb |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd949c120819099a9d56eb71a0339 |
completed | March 7, 2026, 7:52 a.m. |
Created at: March 6, 2026, 9:55 p.m.