Triple

T17164653
Position Surface form Disambiguated ID Type / Status
Subject Pedro Arias Dávila E416576 entity
Predicate birthPlace P1 FINISHED
Object Segovia NE ONNED1

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: [Pedro Arias Dávila, birthPlace, Segovia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Segovia
Context triple: [Pedro Arias Dávila, birthPlace, 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f913c84481908bb5da8bcc6a2e62 completed April 18, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0195428c6c8190a11e3f7c8f6796fe in_progress May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:37 a.m.