Triple
T67367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the French Republic |
E1342
|
entity |
| Predicate | officeReconstitutedIn |
P4213
|
FINISHED |
| Object | 1958 |
—
|
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: 1958 | Statement: [President of the French Republic, officeReconstitutedIn, 1958]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeReconstitutedIn Context triple: [President of the French Republic, officeReconstitutedIn, 1958]
-
A.
officeInvolved
Indicates that a particular office or organizational unit is involved or participates in a specified event, action, or relationship.
-
B.
establishedOffice
Indicates that an entity created or set up an official office or place of operation.
-
C.
reorganizedAs
Indicates that an existing entity has been restructured or reconfigured into a new organizational form or arrangement.
-
D.
leftOffice
Indicates that an entity ceased holding or performing the duties of a particular office or position.
-
E.
office
Indicates that an entity holds or occupies an official position, role, or post within an organization or institution.
- 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_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. |
| PDg | Predicate description generation | batch_69a2509a1c088190b4afa3045455709a |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.