Triple

T10328055
Position Surface form Disambiguated ID Type / Status
Subject Muley Hacén E242809 entity
Predicate spouse P13 FINISHED
Object Aixa E831694 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: Aixa | Statement: [Muley Hacén, spouse, Aixa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aixa
Context triple: [Muley Hacén, spouse, Aixa]
  • A. Aixa chosen
    Aixa was a prominent Nasrid noblewoman of the Emirate of Granada, best known as the politically influential mother of the last Muslim ruler of Granada, Boabdil.
  • B. Azéma
    Azéma is a French surname most notably borne by architect Léon Azéma, known for his contributions to early 20th-century French public architecture.
  • C. Melide
    Melide is a Swiss municipality in the canton of Ticino, known for its scenic location on Lake Lugano and the Swissminiatur open-air miniature park.
  • D. Hamelle
    Hamelle is a French music publishing house known for issuing important late-19th-century works, including major compositions by César Franck.
  • E. Temara
    Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d7cf21e08190bf605daeea0d9dcf completed April 7, 2026, 10:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71dafa9308190ae0d3c34ba0c58b1 completed April 9, 2026, 3:31 a.m.
Created at: April 6, 2026, 11:51 a.m.