Triple

T1686574
Position Surface form Disambiguated ID Type / Status
Subject Voronezh E36454 entity
Predicate hasSisterCity P919 FINISHED
Object Bari E29192 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: Bari | Statement: [Voronezh, hasSisterCity, Bari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bari
Context triple: [Voronezh, hasSisterCity, Bari]
  • A. Bari chosen
    Bari is a major port city in southern Italy that served as an important Allied military hub and logistics center during World War II.
  • B. 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.
  • C. Pescara
    Pescara is a coastal city in the Abruzzo region of central Italy, known for its Adriatic beaches, modern urban layout, and role as a commercial and tourist hub.
  • D. Ancona
    Ancona is a historic port city on Italy’s Adriatic coast, notable for its long-standing Jewish community and role as a commercial and cultural crossroads.
  • E. Livorno
    Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
  • 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_69a886151508819084fa7f1ce6e05577 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6293c368819094ab0f615e418647 completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae516742dc81909915c49b12645c26 completed March 9, 2026, 4:49 a.m.
Created at: March 4, 2026, 7:29 p.m.