Triple
T17246964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grazia Deledda |
E418650
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Cenere |
E943951
|
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: Cenere | Statement: [Grazia Deledda, notableWork, Cenere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cenere Context triple: [Grazia Deledda, notableWork, Cenere]
-
A.
Cenere
chosen
Cenere is a 1916 Italian silent drama film, notable for starring celebrated actress Eleonora Duse in one of her rare screen appearances.
-
B.
Cineriz
Cineriz was an Italian film production and distribution company known for handling prominent auteur films during the mid-20th century.
-
C.
Ceresio
Ceresio is another name for Lake Lugano, a glacial lake in southern Switzerland and northern Italy known for its scenic Alpine surroundings and resort towns.
-
D.
Escoma
Escoma is a small town in Bolivia’s La Paz Department, situated in Camacho Province near the shores of Lake Titicaca.
-
E.
Carboneras
Carboneras is a coastal town in Spain’s Almería province, known for its beaches, fishing heritage, and proximity to the Cabo de Gata-Níjar Natural Park.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e24a4508190bbcc70c36b2b9c13 |
completed | April 19, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170f744d8819099f10bbba364586d |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.