Triple
T8213182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Array |
E191870
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | E.ON |
E235141
|
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: E.ON | Statement: [London Array, developer, E.ON]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: E.ON Context triple: [London Array, developer, E.ON]
-
A.
E.ON
chosen
E.ON is a major European energy company based in Germany that focuses on electricity generation, renewable energy, and energy infrastructure services.
-
B.
RWE
RWE is a major German energy company that operates internationally, with significant investments in renewable power generation such as large offshore wind farms.
-
C.
Siemens Energy
Siemens Energy is a global energy technology company specializing in power generation, transmission, and related services for conventional and renewable energy systems.
-
D.
Ørsted
Ørsted is a Danish renewable energy company and one of the world’s leading developers and operators of offshore wind farms.
-
E.
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.
- 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_69ca82c8c054819087fedd9a5436b8a3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb76e1ffa081908883338e7d3a7c6d |
completed | March 31, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccedea881481909f9348778290eb63 |
completed | April 1, 2026, 10:05 a.m. |
Created at: March 30, 2026, 5:44 p.m.