Triple

T15620431
Position Surface form Disambiguated ID Type / Status
Subject Soria campus E375536 entity
Predicate locatedIn P40 FINISHED
Object Soria E382569 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: Soria | Statement: [Soria campus, locatedIn, Soria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soria
Context triple: [Soria campus, locatedIn, Soria]
  • A. Soria chosen
    Soria is a historic and sparsely populated province in north-central Spain, known for its medieval heritage, natural landscapes, and role within the autonomous community of Castile and León.
  • B. Palencia
    Palencia is a historic city in northwestern Spain known for its Romanesque architecture and role as the capital of the province of the same name.
  • C. Ciudad Real
    Ciudad Real is a historic provincial capital in central Spain known for its location on the Castilian plateau and its connections to the La Mancha region.
  • D. Pozorrubio
    Pozorrubio is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its crop production and rural communities.
  • E. Valverde de la Vera
    Valverde de la Vera is a historic village in the province of Cáceres, Extremadura, Spain, known for its traditional architecture and scenic setting in the La Vera region.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9a95f08190b0013ba1428849d3 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb7c2a6081908e957d39ec056062 completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 4:13 a.m.