Triple
T8155910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | César Award for Best Foreign Film |
E190448
|
entity |
| Predicate | isNonFrenchCategory |
P80860
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [César Award for Best Foreign Film, isNonFrenchCategory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonFrenchCategory Context triple: [César Award for Best Foreign Film, isNonFrenchCategory, true]
-
A.
hasFrenchSector
Indicates that an entity includes, controls, or is associated with a sector or area designated as French.
-
B.
usesPrimaryFrenchGateway
Indicates that an entity routes its primary communications or connections through a main gateway located in or associated with French infrastructure or networks.
-
C.
containsCategory
Indicates that one entity includes or encompasses a specific category as part of its classification or organizational structure.
-
D.
isFrancophoneParty
Indicates that a political party primarily uses French or represents French-speaking communities.
-
E.
isNotIndoEuropean
Indicates that an entity’s language or linguistic affiliation does not belong to the Indo-European language family.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb44d8a37481909397b5cc321b94be |
completed | March 31, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69cb36a0847c8190af9038aef78319b3 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb39ba412881908a053e88f29a9588 |
completed | March 31, 2026, 3:04 a.m. |
Created at: March 30, 2026, 5:37 p.m.