Triple
T7374129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suez |
E170080
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | SUEZ |
E556358
|
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: SUEZ | Statement: [Suez, hasBrand, SUEZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SUEZ Context triple: [Suez, hasBrand, SUEZ]
-
A.
GDF Suez
GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
-
B.
Dalkia
Dalkia is a French energy services company specializing in energy efficiency, district heating and cooling, and sustainable energy solutions for buildings and industry.
-
C.
Tractebel
Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
-
D.
Thales Group
Thales Group is a French multinational company specializing in aerospace, defense, security, and transportation technologies and systems.
-
E.
Compagnie Générale des Eaux
chosen
Compagnie Générale des Eaux was a major French utilities company, historically focused on water services, that evolved into the multinational environmental services group now known as Veolia.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a6643c81909d626c8b6a7a11fd |
completed | March 27, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802ce8e408190946637d04083521c |
completed | March 28, 2026, 4:33 p.m. |
Created at: March 27, 2026, 3:07 p.m.