Triple

T11575517
Position Surface form Disambiguated ID Type / Status
Subject County of Besalú E274492 entity
Predicate notableRuler P22 FINISHED
Object Oliba Cabreta E270103 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: Oliba Cabreta | Statement: [County of Besalú, notableRuler, Oliba Cabreta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oliba Cabreta
Context triple: [County of Besalú, notableRuler, Oliba Cabreta]
  • A. Oliba Cabreta chosen
    Oliba Cabreta was a 10th-century Catalan count who played a key role in consolidating and expanding the power of the counties of Cerdanya and Besalú in the eastern Pyrenees.
  • B. Pardo Villalón
    Pardo Villalón is the compound Spanish surname associated with the Chilean naval officer and Antarctic explorer Luis Pardo.
  • C. La Cabrera
    La Cabrera is a locality in Spain’s Province of León, known for its rural character and setting within the mountainous landscapes of northwestern Castile and León.
  • D. Cruz Villalón
    Cruz Villalón is a Spanish surname notably borne by Antonio Cruz Villalón, a prominent jurist and former Advocate General at the Court of Justice of the European Union.
  • E. Al Olaya
    Al Olaya is a prominent commercial and business district in Riyadh, Saudi Arabia, known for its modern skyscrapers, upscale shopping, and major corporate offices.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d89049721081909278adfada668ef9 completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69e713e49f508190b9bad316d68eab42 completed April 21, 2026, 6:06 a.m.
Created at: April 8, 2026, 9:38 p.m.