Triple

T11135812
Position Surface form Disambiguated ID Type / Status
Subject Yucatán E263405 entity
Predicate contains P35 FINISHED
Object Valladolid E332291 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: [Yucatán, contains, Valladolid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valladolid
Context triple: [Yucatán, contains, Valladolid]
  • A. Valladolid
    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 chosen
    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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e85daddc8190a1ae2a4a75cc8d50 completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e496b4cadc8190b82ac12061c31bdc completed April 19, 2026, 8:47 a.m.
Created at: April 8, 2026, 9:28 p.m.