Triple
T15710830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 8½ |
E380831
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Cineriz |
E539888
|
NE 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: Cineriz | Statement: [8½, productionCompany, Cineriz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cineriz Context triple: [8½, productionCompany, Cineriz]
-
A.
Cineriz
chosen
Cineriz was an Italian film production and distribution company known for handling prominent auteur films during the mid-20th century.
-
B.
Cyanika
Cyanika is a town in northern Rwanda that serves as the administrative center of Burera District.
-
C.
Cenere
Cenere is a 1916 Italian silent drama film, notable for starring celebrated actress Eleonora Duse in one of her rare screen appearances.
-
D.
Nivala
Nivala is a small town and municipality in Northern Ostrobothnia, Finland, known for its rural character and agricultural surroundings.
-
E.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff757d74b481909c8332a09ae36b4f |
completed | May 9, 2026, 5:57 p.m. |
Created at: April 10, 2026, 4:45 a.m.