Triple

T8206523
Position Surface form Disambiguated ID Type / Status
Subject Plovdiv E191700 entity
Predicate hasTwinTown P919 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: [Plovdiv, hasTwinTown, Valencia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valencia
Context triple: [Plovdiv, hasTwinTown, 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 is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
  • C. Valencia
    Valencia is a municipality in the Philippine province of Negros Oriental known for its cool climate, geothermal energy resources, and natural attractions such as waterfalls and mountain landscapes.
  • D. Valencia
    Valencia is a city in Ecuador that serves as the capital of Los Ríos Province’s Valencia Canton and is known for its agricultural surroundings and tropical climate.
  • E. Valencia
    Valencia is a master-planned community in northern Los Angeles County, California, now incorporated into the city of Santa Clarita and known for its residential neighborhoods, shopping centers, and proximity to Six Flags Magic Mountain.
  • 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_69ca82c7f3e08190857bf1fc63b2a10c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb726b520081908ce4a03bd14dfcdf completed March 31, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc69b9b8c819082a164433312166e completed April 2, 2026, 1:30 a.m.
Created at: March 30, 2026, 5:43 p.m.