Triple

T8929721
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Free Zone plant E212620 entity
Predicate operator P179 FINISHED
Object SEAT E37746 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: SEAT | Statement: [Barcelona Free Zone plant, operator, SEAT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SEAT
Context triple: [Barcelona Free Zone plant, operator, SEAT]
  • A. SEAT chosen
    SEAT is a Spanish automobile manufacturer known for producing affordable, stylish cars and operating as a subsidiary of the Volkswagen Group.
  • B. SEAT Tarraco
    The SEAT Tarraco is a mid-size, seven-seat SUV produced by Spanish automaker SEAT, positioned as the brand’s flagship family and crossover model.
  • C. SEAT Toledo
    The SEAT Toledo is a compact family car produced by Spanish automaker SEAT, known for sharing its underpinnings with other Volkswagen Group models.
  • D. SEAT León
    The SEAT León is a compact hatchback car produced by Spanish manufacturer SEAT, known for combining sporty styling and performance with everyday practicality.
  • E. SEAT 127
    SEAT 127 is a Spanish-built supermini car produced by SEAT under license from Fiat, closely based on the Fiat 127 and popular in Spain during the 1970s and early 1980s.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6676d5d881908ce78cbb5561a68b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeb2b4f048190a2d387b64975647a completed April 3, 2026, 4:30 p.m.
Created at: March 30, 2026, 6:57 p.m.