Triple

T15527773
Position Surface form Disambiguated ID Type / Status
Subject Valladolid campus E369126 entity
Predicate locatedIn P40 FINISHED
Object Valladolid E11502 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: Valladolid | Statement: [Valladolid campus, locatedIn, Valladolid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valladolid
Context triple: [Valladolid campus, locatedIn, Valladolid]
  • A. Valladolid chosen
    Valladolid is a historic city in northwestern Spain that served as a major political and cultural center, including as a former capital of the Spanish monarchy.
  • B. Valladolid
    Valladolid is a historic colonial city in Mexico’s Yucatán Peninsula, known for its Spanish architecture, cenotes, and proximity to Mayan archaeological sites.
  • C. Alcalá-Zamora
    Alcalá-Zamora is the surname of Niceto Alcalá-Zamora, a prominent Spanish lawyer and politician who served as the first President of the Second Spanish Republic.
  • D. Burgos
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • E. Burgos
    Burgos is a small coastal municipality on the northern tip of Siargao Island in the Philippines, known for its quiet beaches and surf spots.
  • 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_69d85a1794cc8190b0b428716296e63e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0414620588190958ffde651ccab5f completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d39a0908190a27f7bbaee7a04ef completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:05 a.m.