Triple

T22606640
Position Surface form Disambiguated ID Type / Status
Subject Matarraña comarca E566578 entity
Predicate containsSettlement P847 FINISHED
Object Lledó NE NERFINISHED

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: Lledó | Statement: [Matarraña comarca, containsSettlement, Lledó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lledó
Context triple: [Matarraña comarca, containsSettlement, Lledó]
  • A. Lledó chosen
    Lledó is a small rural village in the Matarranya comarca of eastern Aragon, Spain, known for its traditional architecture and scenic natural surroundings.
  • B. Lanin
    Lanín is a prominent stratovolcano in the Andes on the border between Argentina and Chile, known for its conical snow-capped peak and popularity among climbers.
  • C. Llausha
    Llausha is a village in the municipality of Skenderaj in central Kosovo.
  • D. Tredòs
    Tredòs is a small village in the Val d'Aran region of Catalonia, Spain, known for its traditional Pyrenean architecture and proximity to the Baqueira-Beret ski resort.
  • E. Moianès
    Moianès is a comarca (county) in central Catalonia, Spain, known for its rural landscapes, small historic towns, and karstic plateau terrain.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245884860819081046ce07d5872c4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1627172488190beb87df965498bcc completed April 29, 2026, 1:44 a.m.
Created at: April 17, 2026, 2:54 p.m.