Triple

T14372217
Position Surface form Disambiguated ID Type / Status
Subject Samsung E356383 entity
Predicate subsidiary P258 FINISHED
Object Samsung Biologics E72266 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 Biologics | Statement: [Samsung, subsidiary, Samsung Biologics]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samsung Biologics
Context triple: [Samsung, subsidiary, Samsung Biologics]
  • A. Samsung Biologics chosen
    Samsung Biologics is a South Korean biopharmaceutical company specializing in contract development and manufacturing (CDMO) of biologic drugs for global pharmaceutical and biotech firms.
  • B. Samsung Bioepis
    Samsung Bioepis is a South Korean biopharmaceutical company specializing in the development and commercialization of biosimilar medicines.
  • C. Mitsubishi Tanabe Pharma
    Mitsubishi Tanabe Pharma is a Japanese pharmaceutical company known for developing prescription drugs and biopharmaceuticals, including treatments for neurological and autoimmune diseases.
  • D. Chugai Pharmaceutical
    Chugai Pharmaceutical is a major Japanese research-based pharmaceutical company known for its innovative biopharmaceuticals and strategic alliance with Roche.
  • E. Lonza
    Lonza is a global Swiss-based life sciences company specializing in pharmaceutical, biotech, and nutrition products and services, particularly in contract development and manufacturing.
  • 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.