Triple
T22460422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TotalEnergies SE |
E555213
|
entity |
| Predicate | formerlyKnownAs |
P65
|
FINISHED |
| Object | TotalFinaElf |
—
|
NE NERFINISHED |
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: TotalFinaElf | Statement: [TotalEnergies SE, formerlyKnownAs, TotalFinaElf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TotalFinaElf Context triple: [TotalEnergies SE, formerlyKnownAs, TotalFinaElf]
-
A.
Lefuel
Lefuel is a French surname most notably associated with Hector Lefuel, a 19th-century architect known for his work on the Louvre in Paris.
-
B.
TotalEnergies
chosen
TotalEnergies is a major French multinational energy company engaged in oil, gas, and renewable energy production and distribution worldwide.
-
C.
Flandin
Flandin is a French surname most notably borne by Pierre-Étienne Flandin, a prominent 20th-century French politician and statesman.
-
D.
French Petroleum Institute
The French Petroleum Institute is a French public research and training organization specializing in energy, particularly oil, gas, and petrochemical technologies.
-
E.
Telfrance
Telfrance is a French television production company best known for creating and producing popular TV series and other audiovisual content.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b7eb5688190bd5e41d4d8189668 |
completed | April 29, 2026, 1:14 a.m. |
Created at: April 16, 2026, 8:48 p.m.