Triple
T9576195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Exxon |
E231050
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object | TotalEnergies |
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 | Statement: [Exxon, hasCompetitor, TotalEnergies]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TotalEnergies Context triple: [Exxon, hasCompetitor, TotalEnergies]
-
A.
TotalEnergies
chosen
TotalEnergies is a major French multinational energy company engaged in oil, gas, and renewable energy production and distribution worldwide.
-
B.
Électricité de France
Électricité de France is France’s state-owned electric utility company and one of the world’s largest producers and distributors of electricity, particularly known for its extensive nuclear power fleet.
-
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.
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.
-
E.
Cepsa
Cepsa is a Spanish integrated energy and petrochemical company involved in oil and gas exploration, refining, and the production of chemical products.
- 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_69ca848091c48190bc313d6620d09555 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99ac17a48190bb8448394f22b1e9 |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d152c3f1e8819099f3f9d0f1d2d7b3 |
completed | April 4, 2026, 6:04 p.m. |
Created at: March 30, 2026, 8:05 p.m.