Triple

T3427839
Position Surface form Disambiguated ID Type / Status
Subject Samsung Biologics E72266 entity
Predicate parentCompany P254 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 Biologics, parentCompany, Samsung Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samsung Group
Context triple: [Samsung Biologics, parentCompany, Samsung Group]
  • A. LG Corporation
    LG Corporation is a major South Korean multinational conglomerate with diversified businesses spanning electronics, chemicals, and telecommunications.
  • B. Samsung chosen
    Samsung is a South Korean multinational conglomerate best known globally for its smartphones, consumer electronics, and advanced semiconductor technologies.
  • C. 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.
  • D. 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.
  • E. Samsung Chaebol
    Samsung Chaebol is a major South Korean conglomerate comprising numerous affiliated companies across industries such as electronics, shipbuilding, construction, and finance.
  • 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_69ad85ae14308190bcbc25cfa0246c0b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb983f4608190abcc27aa7b926deb completed March 8, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c36c12008190b21c47091a4e2ca6 completed March 14, 2026, 2:09 a.m.
Created at: March 8, 2026, 3:15 p.m.