Triple

T7667809
Position Surface form Disambiguated ID Type / Status
Subject Real Valladolid E173668 entity
Predicate location 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: [Real Valladolid, location, Valladolid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valladolid
Context triple: [Real Valladolid, location, 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_69c699562484819086752091e3164a27 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701c26ffc8190894fdef92f877f38 completed March 27, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9721e3d488190a7e7d0f0e8d0b97f completed March 29, 2026, 6:40 p.m.
Created at: March 27, 2026, 4 p.m.