Triple

T3427812
Position Surface form Disambiguated ID Type / Status
Subject Samsung Fire & Marine Insurance E72265 entity
Predicate alternateName P39 FINISHED
Object Samsung Fire & Marine E72265 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 Fire & Marine | Statement: [Samsung Fire & Marine Insurance, alternateName, Samsung Fire & Marine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samsung Fire & Marine
Context triple: [Samsung Fire & Marine Insurance, alternateName, Samsung Fire & Marine]
  • A. Samsung Fire & Marine Insurance chosen
    Samsung Fire & Marine Insurance is a major South Korean non-life insurance company offering a wide range of property, casualty, and marine insurance services.
  • B. Atlantic Marine
    Atlantic Marine is a shipbuilding company known for constructing specialized research and commercial vessels.
  • C. Evergreen Marine
    Evergreen Marine is a major Taiwanese container shipping company known for operating one of the world’s largest fleets of container vessels.
  • D. Jersey Marine
    Jersey Marine is a coastal village in South Wales known for its proximity to Swansea Bay and its historic tower landmark.
  • E. Protective Life Corporation
    Protective Life Corporation is a U.S.-based insurance and financial services company known for offering life insurance, annuities, and asset protection products.
  • 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_69b35478448481908e1c0f717d99f992 completed March 13, 2026, 12:04 a.m.
Created at: March 8, 2026, 3:15 p.m.