Triple

T9255069
Position Surface form Disambiguated ID Type / Status
Subject Ørsted E222419 entity
Predicate formerName P65 FINISHED
Object DONG Energy 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: DONG Energy | Statement: [Ørsted, formerName, DONG Energy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DONG Energy
Context triple: [Ørsted, formerName, DONG Energy]
  • 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. E.ON
    E.ON is a major European energy company based in Germany that focuses on electricity generation, renewable energy, and energy infrastructure services.
  • C. DG Energy
    DG Energy is the European Commission department responsible for developing and implementing EU energy policy, including security of supply, sustainability, and the internal energy market.
  • 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. SSE Renewables
    SSE Renewables is a UK-based renewable energy company focused on developing, owning, and operating wind and hydroelectric power assets, particularly offshore wind farms.
  • 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_69ca841e4cd481908e738c74e958eaea completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd06b3c314819096632b8263288aae completed April 1, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09bde36688190bf66669f585dcee7 completed April 4, 2026, 5:04 a.m.
Created at: March 30, 2026, 7:31 p.m.