Triple

T14260775
Position Surface form Disambiguated ID Type / Status
Subject Sala de Contratación E353510 entity
Predicate locatedIn P40 FINISHED
Object Valencia E13494 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: Valencia | Statement: [Sala de Contratación, locatedIn, Valencia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valencia
Context triple: [Sala de Contratación, locatedIn, Valencia]
  • A. Valencia chosen
    Valencia is a major Spanish coastal city known for its historic architecture, vibrant culture, and significant role as a key Mediterranean trade and tourism hub.
  • B. Valencia
    Valencia was the original working title for the 2016 psychological thriller film "10 Cloverfield Lane."
  • C. Valencia
    Valencia is a major inland city in the Philippine province of Bukidnon, known as a commercial and agricultural hub in Northern Mindanao.
  • D. Valencia
    Valencia is a city located in the highland province of Bukidnon in the Philippines, known as a major agricultural and commercial center in the region.
  • E. Valencia
    Valencia is a genus of small, freshwater killifish native to Mediterranean Europe, known for inhabiting coastal streams and threatened aquatic habitats.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de635534988190816fdfb315cd2a3f completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c2e7ee081909a70c9d9b32b6ce5 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:09 a.m.