Triple
T20702768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Third Person |
E508823
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Corsan |
—
|
NE NERFINISHED |
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: Corsan | Statement: [Third Person, productionCompany, Corsan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Corsan Context triple: [Third Person, productionCompany, Corsan]
-
A.
Corsan
chosen
Corsan is a film production company known for financing and producing international feature films.
-
B.
Scandriglia
Scandriglia is a small Italian municipality in the Lazio region, known for its historic hilltop setting and proximity to the Apennine mountains.
-
C.
Garvanza
Garvanza is a historic neighborhood in Northeast Los Angeles known for its early arts community, Craftsman architecture, and role in the development of the Arroyo culture movement.
-
D.
Murasson
Murasson is a small rural commune in southern France’s Aveyron department, characterized by its agricultural landscape and traditional village setting.
-
E.
Seccheto
Seccheto is a small coastal village on the island of Elba in Tuscany, Italy, known for its beaches and seaside tourism.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c18cb9cc819095d0669dca037424 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:13 p.m.