Triple
T15541493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Czernin |
E370487
|
entity |
| Predicate | productionCompanyFocus |
P39595
|
FINISHED |
| Object | feature films |
—
|
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: feature films | Statement: [Pete Czernin, productionCompanyFocus, feature films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productionCompanyFocus Context triple: [Pete Czernin, productionCompanyFocus, feature films]
-
A.
productionCompanyType
chosen
Indicates the specific category or kind of production company associated with a given entity.
-
B.
productionCompanyOfWork
Indicates that a company is responsible for producing a particular creative work (such as a film, TV show, or similar production).
-
C.
productionCompanyRole
Indicates the specific capacity or function an entity fulfills within a production company’s activities or projects.
-
D.
underlyingCompanyBusinessFocus
Indicates the primary industry, sector, or type of business activity that the underlying company is focused on.
-
E.
acquiredCompanyFocus
Indicates that a company’s primary business focus or specialization changed as a result of acquiring another company.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04432c3808190bb5b653bf8de30c6 |
completed | April 16, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:07 a.m.