Triple

T20886096
Position Surface form Disambiguated ID Type / Status
Subject Martigues E514282 entity
Predicate hasTwinTown P919 FINISHED
Object Martinsicuro 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: Martinsicuro | Statement: [Martigues, hasTwinTown, Martinsicuro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martinsicuro
Context triple: [Martigues, hasTwinTown, Martinsicuro]
  • A. Martinsicuro chosen
    Martinsicuro is a coastal town in the Abruzzo region of Italy, known for its Adriatic beaches and tourism.
  • B. Montescaglioso
    Montescaglioso is a historic hill town in the Basilicata region of southern Italy, known for its medieval architecture and ancient monastic complexes.
  • C. Montignoso
    Montignoso is a municipality in Tuscany, central Italy, known for its coastal location near the Ligurian Sea and its proximity to the Apuan Alps.
  • D. Campitello
    Campitello is a small commune in the Haute-Corse department on the island of Corsica in France.
  • E. Rapagnano
    Rapagnano is a small Italian municipality in the Marche region known for its historic hilltop setting and traditional rural character.
  • 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6d058d4dc81908398f8c75e30dc77 completed April 21, 2026, 1:18 a.m.
Created at: April 16, 2026, 12:46 p.m.