Triple

T6684278
Position Surface form Disambiguated ID Type / Status
Subject Puente de Segovia E152061 entity
Predicate namedAfter P63 FINISHED
Object Segovia E151896 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: Segovia | Statement: [Puente de Segovia, namedAfter, Segovia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Segovia
Context triple: [Puente de Segovia, namedAfter, Segovia]
  • A. Segovia chosen
    Segovia is a historic Spanish city in the region of Castile and León, renowned for its Roman aqueduct, medieval architecture, and well-preserved old town.
  • B. Ávila
    Ávila is a historic walled city in central Spain, renowned for its remarkably well-preserved medieval fortifications and Romanesque and Gothic architecture.
  • C. Badajoz
    Badajoz is a historic city in western Spain near the Portuguese border, known for its medieval fortress and role as a strategic frontier stronghold.
  • D. Burgos
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • E. Burgos
    Burgos is a small coastal municipality on the northern tip of Siargao Island in the Philippines, known for its quiet beaches and surf spots.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b122df14819082068af37611b691 completed March 27, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c74237905c8190abb9b98a8c603662 completed March 28, 2026, 2:51 a.m.
Created at: March 27, 2026, 2:04 p.m.