Triple
T7315435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalkia |
E168398
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
Dalkia Biogaz
Dalkia Biogaz is a French energy company subsidiary specializing in the production and management of biogas and renewable energy solutions.
|
E168398
|
NE FINISHED |
How this triple was built (4 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: Dalkia Biogaz | Statement: [Dalkia, hasSubsidiary, Dalkia Biogaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dalkia Biogaz Context triple: [Dalkia, hasSubsidiary, Dalkia Biogaz]
-
A.
Dalkia
Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
-
B.
Veolia Environnement
Veolia Environnement is a French multinational company specializing in water, waste, and energy management services worldwide.
-
C.
GDF Suez
GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
-
D.
Areva
Areva was a French multinational group specializing in nuclear power and renewable energy technologies, known for its involvement in the entire nuclear fuel cycle.
-
E.
Tractebel
Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dalkia Biogaz Triple: [Dalkia, hasSubsidiary, Dalkia Biogaz]
Generated description
Dalkia Biogaz is a French energy company subsidiary specializing in the production and management of biogas and renewable energy solutions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dalkia Biogaz Target entity description: Dalkia Biogaz is a French energy company subsidiary specializing in the production and management of biogas and renewable energy solutions.
-
A.
Dalkia
chosen
Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
-
B.
Veolia Environnement
Veolia Environnement is a French multinational company specializing in water, waste, and energy management services worldwide.
-
C.
GDF Suez
GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
-
D.
Areva
Areva was a French multinational group specializing in nuclear power and renewable energy technologies, known for its involvement in the entire nuclear fuel cycle.
-
E.
Tractebel
Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
- F. None of above.
Provenance (5 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ec04bdfc819093556aa5fa69e0e1 |
completed | March 27, 2026, 8:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eeeedea88190a17cf6b83abc10d8 |
completed | March 28, 2026, 3:08 p.m. |
| NEDg | Description generation | batch_69c7efd351e88190ab5da8977e80c339 |
completed | March 28, 2026, 3:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7f02f95508190a7b323f3f94e4a0f |
completed | March 28, 2026, 3:13 p.m. |
Created at: March 27, 2026, 3:02 p.m.