Triple
T5933358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TotalEnergies |
E131987
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | TotalEnergies Marketing |
E131987
|
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: TotalEnergies Marketing | Statement: [TotalEnergies, hasSubsidiary, TotalEnergies Marketing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TotalEnergies Marketing Context triple: [TotalEnergies, hasSubsidiary, TotalEnergies Marketing]
-
A.
TotalEnergies
chosen
TotalEnergies is a major French multinational energy company engaged in oil, gas, and renewable energy production and distribution worldwide.
-
B.
Sinopec
Sinopec is one of China’s largest state-owned oil and petrochemical companies, engaged in exploration, refining, and marketing of petroleum and chemical products worldwide.
-
C.
PSA Group
PSA Group was a major French automotive manufacturer best known for producing Peugeot, Citroën, and DS vehicles before merging to form Stellantis.
-
D.
MOL Global
MOL Global was a Malaysian online payment solutions provider best known for acquiring the once-popular social networking site Friendster.
-
E.
British Petroleum
British Petroleum is a major British multinational oil and gas company involved in exploration, production, refining, and energy trading worldwide.
- 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0389f6fc881909527b928838ffcdd |
completed | March 22, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c064d2a4819096085668182cfde1 |
completed | March 23, 2026, 4:24 a.m. |
Created at: March 22, 2026, 4 p.m.