Triple
T67387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the French Republic |
E1342
|
entity |
| Predicate | currentHolderTookOfficeOn |
P1814
|
FINISHED |
| Object | 2017-05-14 |
—
|
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: 2017-05-14 | Statement: [President of the French Republic, currentHolderTookOfficeOn, 2017-05-14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentHolderTookOfficeOn Context triple: [President of the French Republic, currentHolderTookOfficeOn, 2017-05-14]
-
A.
officeHolderStartTime
chosen
Indicates the date and time at which an individual begins holding a particular office or position.
-
B.
currentChairStartDate
Indicates the date on which the person’s current term as chair officially began.
-
C.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
D.
firstInOfficeTo
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another entity or context.
-
E.
successorOfficeTo
Indicates that one office or position directly follows and replaces another in an official sequence or hierarchy.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2509b5a088190bb9d2b650aeb8bca |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ea749788190bc17865171ff909a |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.