Triple

T4058662
Position Surface form Disambiguated ID Type / Status
Subject Tarlac E84755 entity
Predicate hasCity P316 FINISHED
Object Gerona E80146 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: Gerona | Statement: [Tarlac, hasCity, Gerona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gerona
Context triple: [Tarlac, hasCity, Gerona]
  • A. Girona chosen
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • B. Lleida
    Lleida is a historic city in western Catalonia, Spain, known for its medieval Seu Vella cathedral and role as a regional agricultural and commercial center.
  • C. Tarragona
    Tarragona is a historic port city in northeastern Spain, renowned for its well-preserved Roman ruins and status as a major cultural and economic center in Catalonia.
  • D. Mataró
    Mataró is a coastal city in northeastern Spain known as an important commercial and industrial center on the Mediterranean near Barcelona.
  • E. Reus
    Reus is a city in Catalonia, Spain, known as the birthplace of architect Antoni Gaudí and for its historic center and vermouth production.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbd13b4481908f9c09cc4f4a9724 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f15f0088190b2ec453183f0ca7f completed March 14, 2026, 3:30 p.m.
Created at: March 9, 2026, 3:38 p.m.