Triple

T17430964
Position Surface form Disambiguated ID Type / Status
Subject Loiri Porto San Paolo E423866 entity
Predicate hasLocality P7943 FINISHED
Object Porto San Paolo 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: Porto San Paolo | Statement: [Loiri Porto San Paolo, hasLocality, Porto San Paolo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porto San Paolo
Context triple: [Loiri Porto San Paolo, hasLocality, Porto San Paolo]
  • A. Porto San Paolo chosen
    Porto San Paolo is a coastal village and tourist resort in northeastern Sardinia, Italy, known for its beaches and proximity to the Tavolara Marine Protected Area.
  • B. Santos city
    Santos city is a coastal municipality in the state of São Paulo, Brazil, best known for its major port and its historic football club Santos FC.
  • C. Atibaia
    Atibaia is a municipality in southeastern Brazil known for its mild climate, flower and strawberry production, and proximity to São Paulo city.
  • D. Barretos
    Barretos is a municipality in the Brazilian state of São Paulo, widely known for hosting one of the largest annual rodeo festivals in Latin America.
  • E. Porto Palermo
    Porto Palermo is a small coastal bay and village in southern Albania known for its scenic shoreline, historic castle, and former military installations.
  • 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4490072b48190a39b1ac7bb5eb035 completed April 19, 2026, 3:16 a.m.
Created at: April 10, 2026, 5:46 a.m.