Triple
T7281749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doğu Perinçek |
E163164
|
entity |
| Predicate | hasBeenCandidateForOffice |
P12344
|
FINISHED |
| Object | President of Turkey |
—
|
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 Turkey | Statement: [Doğu Perinçek, hasBeenCandidateForOffice, President of Turkey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenCandidateForOffice Context triple: [Doğu Perinçek, hasBeenCandidateForOffice, President of Turkey]
-
A.
nominatedForOffice
Indicates that an entity has been formally put forward as a candidate to hold a particular office or position.
-
B.
wasCandidateIn
chosen
Indicates that an entity served as a candidate in a particular election, contest, or selection process.
-
C.
hasPoliticalOfficeScope
Indicates that a political office or position is limited to, defined within, or applicable to a specific jurisdiction, level, or scope of political authority.
-
D.
heldPoliticalOfficeIn
Indicates that an entity served in a political office or position within a specified governmental body or jurisdiction.
-
E.
hasHistoricalOfficeHolder
Indicates that an office, position, or role has been held by a specific person at some point in the past.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb4d3e3c8190a05cb5af5f52bd75 |
completed | March 27, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:59 p.m.