Triple

T16294467
Position Surface form Disambiguated ID Type / Status
Subject Citroën ZX E395610 entity
Predicate assemblyLocation P40 FINISHED
Object Vigo, Spain E189114 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: Vigo, Spain | Statement: [Citroën ZX, assemblyLocation, Vigo, Spain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vigo, Spain
Context triple: [Citroën ZX, assemblyLocation, Vigo, Spain]
  • A. Vigo chosen
    Vigo is a major industrial and port city in northwestern Spain, known for its shipbuilding, fishing industry, and location on the Atlantic coast of Galicia.
  • B. Vigo
    Vigo is a money transfer service brand that facilitates international remittances, particularly for customers sending funds to Latin America and other global regions.
  • C. Pontevedra
    Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
  • D. Pontevedra
    Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
  • E. Valladolid, Spain
    Valladolid, Spain is a historic city in northwestern Spain that served as a former capital of the Spanish Empire and is known for its rich cultural heritage and architecture.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e25e2c255881909d99c43770475329 completed April 17, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f9965b8819080278ccef15288aa completed May 10, 2026, 6:03 a.m.
Created at: April 10, 2026, 5:05 a.m.