Triple

T8809476
Position Surface form Disambiguated ID Type / Status
Subject Eastern Iberian Peninsula E209620 entity
Predicate majorPortCity P2994 FINISHED
Object Tarragona E80788 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: Tarragona | Statement: [Eastern Iberian Peninsula, majorPortCity, Tarragona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarragona
Context triple: [Eastern Iberian Peninsula, majorPortCity, Tarragona]
  • A. Tarragona chosen
    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.
  • B. Mataró
    Mataró is a coastal city in northeastern Spain known as an important commercial and industrial center on the Mediterranean near Barcelona.
  • C. 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.
  • D. Girona
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • E. Alicante
    Alicante is a historic Mediterranean port city in southeastern Spain known for its beaches, castle-topped hill, and role as a major tourist and commercial 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_69ca8363f3308190a47e3f1ebd51f613 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fd69df4819091e9a7dad87265a4 completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf892b813481909739f72ffd080f49 completed April 3, 2026, 9:32 a.m.
Created at: March 30, 2026, 6:45 p.m.