Triple

T11096261
Position Surface form Disambiguated ID Type / Status
Subject DG ENER E262386 entity
Predicate abbreviation P43 FINISHED
Object DG ENER E262386 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: DG ENER | Statement: [DG ENER, abbreviation, DG ENER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DG ENER
Context triple: [DG ENER, abbreviation, DG ENER]
  • A. DG ENER chosen
    DG ENER is the European Commission department responsible for developing and implementing EU energy policy, including security of supply, sustainability, and the internal energy market.
  • B. 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.
  • C. Energetica
    Energetica is an interactive exhibition at Amsterdam’s NEMO Science Museum that explores the principles and applications of sustainable energy and natural forces.
  • D. Energodar
    Energodar is a Ukrainian city best known for hosting the Zaporizhzhia Nuclear Power Plant, the largest nuclear power station in Europe.
  • E. Rénergie
    Rénergie is a premium anti-aging skincare line by Lancôme known for its lifting, firming, and wrinkle-reducing treatments.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a0897188190b6c293b44990b3d4 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7eca9bc8190b43bae081d97d804 completed April 18, 2026, 8:22 p.m.
Created at: April 8, 2026, 9:27 p.m.