Triple

T1975463
Position Surface form Disambiguated ID Type / Status
Subject Walney Wind Farm E42899 entity
Predicate owner P347 FINISHED
Object Ørsted E222419 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: Ørsted | Statement: [Walney Wind Farm, owner, Ørsted]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ørsted
Context triple: [Walney Wind Farm, owner, Ørsted]
  • A. Ørsted chosen
    Ørsted is a Danish renewable energy company and one of the world’s leading developers and operators of offshore wind farms.
  • B. EDF Renewables
    EDF Renewables is a global renewable energy company specializing in the development, construction, and operation of wind, solar, and energy storage projects.
  • C. RWE
    RWE is a major German energy company that operates internationally, with significant investments in renewable power generation such as large offshore wind farms.
  • D. Engie
    Engie is a major French multinational utility company specializing in electricity, natural gas, and energy services, with a strong focus on renewable and low-carbon energy solutions.
  • E. Vattenfall
    Vattenfall is a Swedish state-owned energy company that is one of Europe’s largest producers and distributors of electricity and heat, with a significant focus on renewable energy such as wind power.
  • 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_69a8871289048190b00b0d7744b7b2b1 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3f835108190b0709ccf3a487a96 completed March 7, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae2702954c8190b95de378e263574a completed March 9, 2026, 1:48 a.m.
Created at: March 4, 2026, 7:36 p.m.