Triple

T5826941
Position Surface form Disambiguated ID Type / Status
Subject Extremaduran language E129249 entity
Predicate region P40 FINISHED
Object Las Hurdes E220274 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: Las Hurdes | Statement: [Extremaduran language, region, Las Hurdes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Las Hurdes
Context triple: [Extremaduran language, region, Las Hurdes]
  • A. Las Hurdes chosen
    Las Hurdes is a remote, mountainous comarca in western Spain known for its rugged landscapes, isolated villages, and historical reputation for poverty and hardship.
  • B. Las Médulas
    Las Médulas is an ancient Roman gold-mining landscape in northwestern Spain, renowned for its dramatic red-earth formations and extensive archaeological remains.
  • C. Cantarranas
    Cantarranas is a small, historic town in central Honduras known for its colorful street murals and traditional cultural festivals.
  • D. Tasqueña
    Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
  • E. Calvero
    Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
  • 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_69c00849d55481908b4f9f5543e0bf6d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0341df8dc8190871af068e1f927a2 completed March 22, 2026, 6:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0985e3e748190abcc226abdcdb4b5 completed March 23, 2026, 1:33 a.m.
Created at: March 22, 2026, 3:53 p.m.