Triple

T22072902
Position Surface form Disambiguated ID Type / Status
Subject San Carlino E545453 entity
Predicate nickname P55 FINISHED
Object San Carlino 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: San Carlino | Statement: [San Carlino, nickname, San Carlino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Carlino
Context triple: [San Carlino, nickname, San Carlino]
  • A. San Carlino chosen
    San Carlino is a small but highly influential Baroque church in Rome designed by architect Francesco Borromini, renowned for its innovative geometry and dynamic architectural forms.
  • B. San Martino
    San Martino is a small locality within the municipality of Bucine in the Tuscany region of Italy.
  • C. San Donaci
    San Donaci is a small town and comune in the Apulia region of southern Italy, known for its agricultural economy and production of wine and olive oil.
  • D. San Gerardo
    San Gerardo is a small municipality in eastern El Salvador known for its rural character and location within the San Miguel Department.
  • E. San Pantaleo
    San Pantaleo is a picturesque village in northeastern Sardinia, Italy, known for its traditional stone houses, artists’ community, and dramatic granite mountain scenery near the Costa Smeralda.
  • 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_69e11e344dfc81909b1d88a7221329c7 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12889f504819089830202e64d97b0 completed April 28, 2026, 9:37 p.m.
Created at: April 16, 2026, 8:28 p.m.