Triple

T14372339
Position Surface form Disambiguated ID Type / Status
Subject KOSPI E356386 entity
Predicate includes P1393 FINISHED
Object POSCO E375833 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: POSCO | Statement: [KOSPI, includes, POSCO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: POSCO
Context triple: [KOSPI, includes, POSCO]
  • A. POSCO Holdings chosen
    POSCO Holdings is a South Korean multinational steelmaking and materials conglomerate that serves as the holding company of the POSCO group, one of the world’s largest steel producers.
  • B. Hanwha Group
    Hanwha Group is a major South Korean conglomerate with diversified businesses spanning chemicals, energy, defense, finance, and construction.
  • C. SK Group
    SK Group is one of South Korea’s largest conglomerates, with diversified businesses spanning energy, telecommunications, semiconductors, and chemicals.
  • D. Hanwha Engineering & Construction
    Hanwha Engineering & Construction is a South Korean construction and engineering company known for undertaking large-scale international projects, including major stadiums and infrastructure developments.
  • E. Hyundai Heavy Industries
    Hyundai Heavy Industries is a South Korean multinational conglomerate best known as one of the world’s largest shipbuilding and heavy industrial engineering companies.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fb2082c8190b42cc5f2bab4f574 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c5363a081909681b54c1d8218dc completed May 8, 2026, 2:37 a.m.
Created at: April 10, 2026, 1:15 a.m.