Triple
T24730317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2007 French presidential election |
E618264
|
entity |
| Predicate | electedPresidentTermNumber |
P142476
|
FINISHED |
| Object | one |
—
|
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: one | Statement: [2007 French presidential election, electedPresidentTermNumber, one]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electedPresidentTermNumber Context triple: [2007 French presidential election, electedPresidentTermNumber, one]
-
A.
presidentNumberElected
chosen
Indicates the ordinal number corresponding to the sequence in which a person was elected president.
-
B.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
-
C.
presidentAtStartOfTerm
Indicates that the subject was the president holding office at the beginning of the specified term or period.
-
D.
termCountAsPresident
Indicates the number of terms an individual has served in the role of president.
-
E.
presidentOfTheRepublicDuringTerm
Indicates that one person holds the office of president of the republic for the duration of a specified term.
- 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.