Triple

T15337413
Position Surface form Disambiguated ID Type / Status
Subject Taifa of Badajoz E366702 entity
Predicate capital P234 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: [Taifa of Badajoz, capital, Badajoz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Badajoz
Context triple: [Taifa of Badajoz, capital, 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e11b22c81908280efe65acd5454 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8757325c8190ad97f50368862ca5 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 3:17 a.m.