Triple
T15746768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Ponta |
E381739
|
entity |
| Predicate | servedUnderOffice |
P37487
|
FINISHED |
| Object | President of Romania |
—
|
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: President of Romania | Statement: [Victor Ponta, servedUnderOffice, President of Romania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedUnderOffice Context triple: [Victor Ponta, servedUnderOffice, President of Romania]
-
A.
servedInOfficeTo
Indicates that one entity held and performed the duties of a particular office or position for the benefit or under the authority of another entity.
-
B.
servesAsOfficeOf
Indicates that one entity functions as the official office, headquarters, or administrative base for another entity.
-
C.
officeHolderServedUnder
chosen
Indicates that a person holding an office served in that role under the authority, administration, or leadership of another specified office holder or leader.
-
D.
servedAs
Indicates that one entity held and performed the role, position, or function associated with another entity for some period of time.
-
E.
succeededInOffice
Indicates that one officeholder directly followed another in holding the same official position.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.