Triple
T1467464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La République En Marche! |
E27056
|
entity |
| Predicate | wonElectionWith |
P4036
|
FINISHED |
| Object | Emmanuel Macron in the 2017 French presidential election |
—
|
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: Emmanuel Macron in the 2017 French presidential election | Statement: [La République En Marche!, wonElectionWith, Emmanuel Macron in the 2017 French presidential election]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonElectionWith Context triple: [La République En Marche!, wonElectionWith, Emmanuel Macron in the 2017 French presidential election]
-
A.
electedWith
chosen
Indicates that one entity attained an elected position or office together with, or as part of the same electoral outcome as, another entity.
-
B.
wonPrimary
Indicates that a candidate secured victory in a primary election against their competitors.
-
C.
wonPresidentialElection
Indicates that one entity achieved victory over others in a presidential election.
-
D.
wonFor
Indicates that one entity received an award, prize, or recognition specifically on behalf of or representing another entity.
-
E.
electoralSuccess
Indicates that an entity has achieved a favorable or winning outcome in an election or electoral process.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5bcfa0881909d6137c69825bc7a |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.