Triple
T24730331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2007 French presidential election |
E618264
|
entity |
| Predicate | farLeftCandidate |
P157050
|
FINISHED |
| Object | Arlette Laguiller |
—
|
NE NERFINISHED |
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: Arlette Laguiller | Statement: [2007 French presidential election, farLeftCandidate, Arlette Laguiller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: farLeftCandidate Context triple: [2007 French presidential election, farLeftCandidate, Arlette Laguiller]
-
A.
farLeftCandidate
chosen
Indicates that the subject is a political candidate positioned at the extreme left of the political spectrum.
-
B.
farRightCandidate
Indicates that the subject is a political candidate aligned with far-right ideologies or positions.
-
C.
mainRightCandidate
Indicates that an entity is the primary or preferred candidate positioned on the right side relative to another reference entity or context.
-
D.
featuredCandidate
Indicates that a particular candidate is highlighted or given special prominence relative to others.
-
E.
firstBallotCandidate
Indicates that the entity was a candidate in the first ballot of an election or selection 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:02 a.m.