Triple
T27281145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Castex |
E688333
|
entity |
| Predicate | termInOfficeIncludesEvent |
P17853
|
FINISHED |
| Object | COVID-19 pandemic in France |
—
|
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: COVID-19 pandemic in France | Statement: [Jean Castex, termInOfficeIncludesEvent, COVID-19 pandemic in France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termInOfficeIncludesEvent Context triple: [Jean Castex, termInOfficeIncludesEvent, COVID-19 pandemic in France]
-
A.
termInOfficeContext
Indicates that one entity’s tenure or period of holding an office, role, or position is being specified or contextualized in relation to another entity or timeframe.
-
B.
termInOffice
Indicates the period during which an individual officially holds a particular office or position.
-
C.
notableEventDuringTerm
chosen
Indicates that a significant or noteworthy event occurred during the time span of a particular term in office or period of service.
-
D.
termWon
Indicates that a particular term, candidate, or entity has achieved victory or success in a specified contest, election, or competitive context.
-
E.
governmentDuringTerm
Indicates that a particular government is the one in power during a specified officeholder’s 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_69ef355998e08190bdff849e8f33adce |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 27, 2026, 11:07 a.m.