Triple
T4693378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Party of the Democratic Revolution |
E104084
|
entity |
| Predicate | hasWonOffice |
P30303
|
FINISHED |
| Object | governorships in Mexican states |
—
|
LITERAL 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: governorships in Mexican states | Statement: [Party of the Democratic Revolution, hasWonOffice, governorships in Mexican states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonOffice Context triple: [Party of the Democratic Revolution, hasWonOffice, governorships in Mexican states]
-
A.
succeededInOffice
Indicates that one officeholder directly followed another in holding the same official position.
-
B.
nominatedForOffice
Indicates that an entity has been formally put forward as a candidate to hold a particular office or position.
-
C.
wonPresidentialElection
Indicates that one entity achieved victory over others in a presidential election.
-
D.
wonPresidencyWith
Indicates that one entity attained the presidency by means of, or through the support, strategy, or circumstances provided by, another entity.
-
E.
hasHeldOfficeType
chosen
Indicates that an entity has at some time occupied or served in a specified type or category of office or position.
- F. None of above.
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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.