Triple
T25716740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeunes avec Macron |
E644882
|
entity |
| Predicate | supportsPerson |
P1853
|
FINISHED |
| Object | candidates of Macronist parties |
—
|
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: candidates of Macronist parties | Statement: [Jeunes avec Macron, supportsPerson, candidates of Macronist parties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPerson Context triple: [Jeunes avec Macron, supportsPerson, candidates of Macronist parties]
-
A.
supportedPeople
Indicates that one entity has provided assistance, backing, or help to another person or group of people.
-
B.
supportsUsers
Indicates that one entity provides assistance, functionality, or compatibility for the users associated with another entity.
-
C.
support
chosen
Indicates that one entity provides assistance, endorsement, or backing to another entity or its actions.
-
D.
supportAgainst
Indicates providing help, resources, or advocacy to oppose or resist a particular target, threat, or adversary.
-
E.
supportCharacter
Indicates that one entity provides assistance, backing, or reinforcement to another entity in performing an action or fulfilling a role.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 21, 2026, 9:43 p.m.