Triple

T5819608
Position Surface form Disambiguated ID Type / Status
Subject Samsung Techwin E129074 entity
Predicate formerParentCompany P5815 FINISHED
Object Samsung Group E13776 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: Samsung Group | Statement: [Samsung Techwin, formerParentCompany, Samsung Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samsung Group
Context triple: [Samsung Techwin, formerParentCompany, Samsung Group]
  • A. LG Corporation
    LG Corporation is a major South Korean multinational conglomerate with diversified businesses spanning electronics, chemicals, and telecommunications.
  • B. Hanwha Group
    Hanwha Group is a major South Korean conglomerate with diversified businesses spanning chemicals, energy, defense, finance, and construction.
  • C. LG Group
    LG Group is a major South Korean multinational conglomerate known for its electronics, chemicals, and telecommunications businesses.
  • D. Samsung chosen
    Samsung is a South Korean multinational conglomerate best known globally for its smartphones, consumer electronics, and advanced semiconductor technologies.
  • E. Samsung C&T
    Samsung C&T is a South Korean construction and trading company known for executing major global projects, including landmark skyscrapers and large-scale infrastructure.
  • 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_69c0084869e881908d7859492183ca7b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c033e477c08190a8bd37c879e6b6b8 completed March 22, 2026, 6:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0e20c208190b861fa8066852efc completed March 23, 2026, 3:17 a.m.
Created at: March 22, 2026, 3:53 p.m.