Triple

T8604337
Position Surface form Disambiguated ID Type / Status
Subject Castro Verde E203759 entity
Predicate locatedNear P294 FINISHED
Object Ourique E199966 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: Ourique | Statement: [Castro Verde, locatedNear, Ourique]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ourique
Context triple: [Castro Verde, locatedNear, Ourique]
  • A. Ourique chosen
    Ourique is a rural municipality in Portugal’s Alentejo region, known for its historical links to the legendary Battle of Ourique and its traditional agricultural landscape.
  • B. Odeleite
    Odeleite is a civil parish in the Algarve region of southern Portugal, known for its rural landscape and proximity to the Guadiana River.
  • C. Echenique
    Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
  • D. Ourcq
    Ourcq is a Paris Métro station in the 19th arrondissement, located near the Canal de l'Ourcq.
  • E. Sombrerete
    Sombrerete is a historic mining town and municipality in the Mexican state of Zacatecas, known for its colonial architecture and surrounding natural landscapes.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46dd8ff8819081ef269192047488 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8f8dfa4819080c8ed475a84be41 completed April 2, 2026, 5:35 p.m.
Created at: March 30, 2026, 6:24 p.m.