Triple
T67385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the French Republic |
E1342
|
entity |
| Predicate | firstHolderTookOfficeIn |
P291
|
FINISHED |
| Object | 1848 |
—
|
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: 1848 | Statement: [President of the French Republic, firstHolderTookOfficeIn, 1848]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstHolderTookOfficeIn Context triple: [President of the French Republic, firstHolderTookOfficeIn, 1848]
-
A.
firstInOfficeTo
chosen
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another entity or context.
-
B.
officeHolderStartTime
Indicates the date and time at which an individual begins holding a particular office or position.
-
C.
presidentInaugurated
Indicates that an individual formally assumes the office of president through an official inauguration event at a specific time and place.
-
D.
firstUsedInElection
Indicates that something (such as a method, technology, or rule) was used for the first time in a particular election.
-
E.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
- 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.