Triple

T11782473
Position Surface form Disambiguated ID Type / Status
Subject Wilmington Assembly Plant E280183 entity
Predicate brandProduced P4022 FINISHED
Object Daewoo E432266 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: Daewoo | Statement: [Wilmington Assembly Plant, brandProduced, Daewoo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daewoo
Context triple: [Wilmington Assembly Plant, brandProduced, Daewoo]
  • A. Daewoo chosen
    Daewoo is a South Korean automotive brand known for producing a range of affordable passenger vehicles and later becoming part of General Motors' global operations.
  • B. LG Electronics
    LG Electronics is a South Korean multinational electronics company known for producing a wide range of consumer electronics, home appliances, and mobile devices.
  • C. Hyundai Electronics
    Hyundai Electronics was a major South Korean semiconductor and electronics manufacturer that later became SK hynix, one of the world’s leading memory chip producers.
  • D. Sanyo
    Sanyo is a Japanese electronics brand known for producing a wide range of consumer and industrial electronic products, including televisions, batteries, and home appliances.
  • E. LG Corporation
    LG Corporation is a major South Korean multinational conglomerate with diversified businesses spanning electronics, chemicals, and telecommunications.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a58413048190b9e3b9d2f5383ec3 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f090c828f0819097662c048542b5da completed April 28, 2026, 10:49 a.m.
Created at: April 8, 2026, 9:42 p.m.