Triple

T11558543
Position Surface form Disambiguated ID Type / Status
Subject UNGSC E274074 entity
Predicate location P40 FINISHED
Object Valencia, Spain 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, Spain | Statement: [UNGSC, location, Valencia, Spain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valencia, Spain
Context triple: [UNGSC, location, Valencia, Spain]
  • 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 small genus of freshwater killifish native to the Mediterranean region of Europe, known for its conservation concern and placement in its own family, Valenciidae.
  • 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88a888e8481909386009b9603e4d3 completed April 10, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e87953088190b72d0afeb9251535 completed April 21, 2026, 3:01 a.m.
Created at: April 8, 2026, 9:37 p.m.