Triple
T11337613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Secretariat of Energy (Mexico) |
E268509
|
entity |
| Predicate | hasAcronym |
P43
|
FINISHED |
| Object | SENER |
E918381
|
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: SENER | Statement: [Secretariat of Energy (Mexico), hasAcronym, SENER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SENER Context triple: [Secretariat of Energy (Mexico), hasAcronym, SENER]
-
A.
SENER
chosen
SENER is Mexico’s federal government ministry responsible for national energy policy, including the regulation and development of the country’s oil, gas, and electricity sectors.
-
B.
SANEF
SANEF is a major French motorway concession and operating company responsible for managing and maintaining several toll highways in northern and eastern France.
-
C.
SERNANP
SERNANP is Peru’s national authority responsible for managing and conserving the country’s system of protected natural areas.
-
D.
Senesky
Senesky is a surname most notably associated with George Senesky, an American professional basketball player and coach in the mid-20th century.
-
E.
SEV
SEV is the National Rail station code for Sevenoaks railway station in Kent, England.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea008b5081908e6c6c6fc29ef936 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5432abfd081909d1bbf6460643fb9 |
completed | April 19, 2026, 9:03 p.m. |
Created at: April 8, 2026, 9:33 p.m.