Triple

T3346166
Position Surface form Disambiguated ID Type / Status
Subject Gothic silk exchange E70379 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: [Gothic silk exchange, locatedIn, Valencia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valencia
Context triple: [Gothic silk exchange, 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 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.
  • C. 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.
  • D. Valencia
    Valencia is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
  • E. Alicante
    Alicante is a historic Mediterranean port city in southeastern Spain known for its beaches, castle-topped hill, and role as a major tourist and commercial center.
  • 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1f4ff888190bf14b9b7fbe9bcee completed March 8, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fae497588190b8f4d23d2925ad9b completed March 14, 2026, 6:06 a.m.
Created at: March 8, 2026, 3:12 p.m.