Triple
T12601611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cepsa |
E300869
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Cepsa |
E300869
|
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: Cepsa | Statement: [Cepsa, hasBrand, Cepsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cepsa Context triple: [Cepsa, hasBrand, Cepsa]
-
A.
Cepsa
chosen
Cepsa is a Spanish integrated energy and petrochemical company involved in oil and gas exploration, refining, and the production of chemical products.
-
B.
Alianza Petrolera
Alianza Petrolera is a professional Colombian football club that competes in the country’s top division, Categoría Primera A.
-
C.
Uniper
Uniper is a German energy company focused on power generation and global energy trading, formed from the conventional energy business spun off from E.ON.
-
D.
Endesa
Endesa is a major Spanish electric utility company and one of the leading energy providers in the Iberian Peninsula and Latin America.
-
E.
TotalEnergies
TotalEnergies is a major French multinational energy company engaged in oil, gas, and renewable energy production and distribution 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954d1f6ac8190ab21ca7bcbc80129 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f66869c0b08190b13bcebbe354cd98 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:09 p.m.