Triple

T8041724
Position Surface form Disambiguated ID Type / Status
Subject Lady of Elche E187455 entity
Predicate locationFound P80705 FINISHED
Object Elche E212865 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: Elche | Statement: [Lady of Elche, locationFound, Elche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elche
Context triple: [Lady of Elche, locationFound, Elche]
  • A. Elche chosen
    Elche is a historic city in southeastern Spain renowned for its vast palm grove, a UNESCO World Heritage Site, and its cultural traditions such as the Mystery Play of Elche.
  • B. Orihuela
    Orihuela is a historic city in southeastern Spain known for its rich medieval heritage, religious architecture, and role as a regional cultural center.
  • C. León
    León is a historic and successful Mexican professional football club known for its multiple Liga MX titles and passionate fan base.
  • D. León
    León is a historic city and former kingdom in northwestern Spain, renowned for its medieval architecture and significant role in the formation of the Spanish state.
  • E. León
    León is a historic city in western Nicaragua known for its colonial architecture, vibrant cultural life, and role as an intellectual and political center of the country.
  • 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_69ca82b00cb48190b59a300f70e97bd7 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f1e98508190a29a7bb5055f8ba0 completed March 31, 2026, 3:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc5706a4a881909758ea34cf5c0cf2 completed March 31, 2026, 11:21 p.m.
Created at: March 30, 2026, 5:23 p.m.