Triple

T9239229
Position Surface form Disambiguated ID Type / Status
Subject Diamond Plaza E222014 entity
Predicate owner P347 FINISHED
Object Posco Group 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 Group | Statement: [Diamond Plaza, owner, Posco Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Posco Group
Context triple: [Diamond Plaza, owner, Posco Group]
  • 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. Lotte Group
    Lotte Group is a major South Korean-Japanese multinational conglomerate with diverse businesses spanning food, retail, tourism, chemicals, and entertainment.
  • E. 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.
  • 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_69ca83ee26cc81909ac624e190597d6d completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccf0a1e49081909c188f1e1e87039b completed April 1, 2026, 10:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d077db03048190b9c1f0812da21733 completed April 4, 2026, 2:30 a.m.
Created at: March 30, 2026, 7:30 p.m.