Triple

T22359028
Position Surface form Disambiguated ID Type / Status
Subject Torrenova E552729 entity
Predicate near P350 FINISHED
Object Palmanova 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: Palmanova | Statement: [Torrenova, near, Palmanova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palmanova
Context triple: [Torrenova, near, Palmanova]
  • A. Palmanova chosen
    Palmanova is a distinctive Renaissance-era star-shaped fortress town in northeastern Italy, renowned for its perfectly symmetrical radial layout and military architecture.
  • B. Palmanova
    Palmanova is a popular beach resort town on the southwest coast of Mallorca, Spain, known for its sandy bays and family-friendly tourism.
  • C. Caerano di San Marco
    Caerano di San Marco is a municipality in the Veneto region of northern Italy, known for its role in the local footwear and sportswear industry.
  • D. Castelvenere
    Castelvenere is a small Italian municipality in the Campania region, noted for its wine production and rural character.
  • E. Monfalcone
    Monfalcone is an industrial port town in northeastern Italy, known for its major shipbuilding industry and location on the Gulf of Trieste.
  • 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_69e11e4affcc8190ba7c27d29062558d completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157d2b9fc81909e09a1c48664b895 completed April 29, 2026, 12:58 a.m.
Created at: April 16, 2026, 8:44 p.m.