Triple

T7554066
Position Surface form Disambiguated ID Type / Status
Subject E80 E178612 entity
Predicate passesThroughCity P416 FINISHED
Object Badajoz E184815 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: Badajoz | Statement: [E80, passesThroughCity, Badajoz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Badajoz
Context triple: [E80, passesThroughCity, Badajoz]
  • A. Badajoz chosen
    Badajoz is a historic city in western Spain near the Portuguese border, known for its medieval fortress and role as a strategic frontier stronghold.
  • B. Burgos
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • C. 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.
  • D. Béjar
    Béjar is a historic town in the province of Salamanca, Spain, known for its textile heritage and scenic setting in the Sierra de Béjar mountains.
  • E. Ávila
    Ávila is a historic walled city in central Spain, renowned for its remarkably well-preserved medieval fortifications and Romanesque and Gothic architecture.
  • 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_69c69f2da22c8190a50942ac20af70e8 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8b990148190b26a3a262cf538b3 completed March 27, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c96c14aa588190a660de4e356a6b07 completed March 29, 2026, 6:14 p.m.
Created at: March 27, 2026, 3:49 p.m.