Triple
T25131946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the Senate of France in 2008 |
E629544
|
entity |
| Predicate | officeHolderChangeYear |
P167042
|
FINISHED |
| Object | 2008 |
—
|
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: 2008 | Statement: [President of the Senate of France in 2008, officeHolderChangeYear, 2008]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderChangeYear Context triple: [President of the Senate of France in 2008, officeHolderChangeYear, 2008]
-
A.
yearOfGovernmentChange
Indicates the specific year in which a government was replaced, overthrown, or otherwise changed.
-
B.
presidentialTermChangeYear
Indicates the year in which a change of presidential term occurs, such as when one president’s term ends and another’s begins.
-
C.
officeHolderBecame
Indicates that an individual assumed or transitioned into holding a particular office or official position.
-
D.
officeHolderAtTime
Indicates that a person holds or held a particular office or position during a specified time period.
-
E.
officeHolderAsOf
Indicates that a person holds or held a specific office or position as of a particular date or point in time.
- F. None of above. chosen
Provenance (4 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6653ccf648190b65fb1141928e47e |
completed | May 2, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 18, 2026, 6:28 a.m.