Triple
T10666958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DG CLIMA |
E251380
|
entity |
| Predicate | worksWith |
P398
|
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 CLIMA, worksWith, DG ENER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DG ENER Context triple: [DG CLIMA, worksWith, 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6f3204bac8190b9bd8bfcc705b06b |
completed | April 9, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a9ceea08190944354d127f2c73b |
completed | April 10, 2026, 10:33 p.m. |
Created at: April 8, 2026, 9:08 p.m.