Triple

T16694933
Position Surface form Disambiguated ID Type / Status
Subject Lanxess Arena E405689 entity
Predicate namedAfter P63 FINISHED
Object Lanxess AG E777205 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: Lanxess AG | Statement: [Lanxess Arena, namedAfter, Lanxess AG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lanxess AG
Context triple: [Lanxess Arena, namedAfter, Lanxess AG]
  • A. Lanxess chosen
    Lanxess is a German specialty chemicals company known for producing high-performance plastics, rubber, and chemical intermediates for various industrial applications.
  • B. BASF
    BASF is a major German chemical company and one of the world's largest producers of chemicals and related 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. Ineos
    Ineos is a large multinational chemicals and energy company based in the United Kingdom, known for its extensive portfolio of petrochemical, oil, gas, and manufacturing operations worldwide.
  • E. SABIC
    SABIC is a major Saudi-based global petrochemicals and plastics manufacturer known as one of the world’s largest chemical companies.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37eacfa788190a8d2058f96c0d445 completed April 18, 2026, 12:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00919acd308190a3f29040554b9cfc completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:19 a.m.