Triple

T10068761
Position Surface form Disambiguated ID Type / Status
Subject BASF E213163 entity
Predicate hasSubsidiary P254 FINISHED
Object BASF Corporation E213163 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: BASF Corporation | Statement: [BASF, hasSubsidiary, BASF Corporation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BASF Corporation
Context triple: [BASF, hasSubsidiary, BASF Corporation]
  • A. BASF chosen
    BASF is a major German chemical company and one of the world's largest producers of chemicals and related products.
  • B. Dow Chemical Company
    Dow Chemical Company is a major American multinational chemical corporation known for producing a wide range of industrial, agricultural, and consumer chemical products.
  • C. Celanese Corporation
    Celanese Corporation is a global specialty materials and chemical company known for producing engineered materials, acetyl products, and other advanced polymers for industrial and consumer applications.
  • D. Lanxess
    Lanxess is a German specialty chemicals company known for producing high-performance plastics, rubber, and chemical intermediates for various industrial applications.
  • E. Rohm and Haas
    Rohm and Haas is a specialty chemicals company known for producing advanced materials and chemical products used in coatings, electronics, and industrial applications.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcff8d9c08190bc030f1dcc696310 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b63d13fc8190bdeac3c7b2529052 completed April 5, 2026, 7:21 p.m.
Created at: March 30, 2026, 8:58 p.m.