Triple

T4959596
Position Surface form Disambiguated ID Type / Status
Subject Canosa di Puglia E111370 entity
Predicate hasNearbyCity P350 FINISHED
Object Barletta E485063 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: Barletta | Statement: [Canosa di Puglia, hasNearbyCity, Barletta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barletta
Context triple: [Canosa di Puglia, hasNearbyCity, Barletta]
  • A. Barletta chosen
    Barletta is a historic coastal city in the Apulia region of southern Italy, known for its medieval architecture and role as a provincial capital.
  • B. Taranto
    Taranto is a historic coastal city in southern Italy known as a major naval and commercial hub and for its strategic position on the Gulf of Taranto.
  • C. Trani
    Trani is a historic coastal city in the Apulia region of southern Italy, known for its medieval architecture and picturesque harbor on the Adriatic Sea.
  • D. Brindisi
    Brindisi is a historic port city in southern Italy’s Apulia region, long serving as a key maritime gateway between Italy and the eastern Mediterranean.
  • E. Cosenza
    Cosenza is a historic city in southern Italy known for its medieval old town, cultural heritage, and role as an important provincial and university center.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71d957cc8190b82fdd1ca61924bf completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9244fb008190baee4ade5b00691f completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:32 p.m.