Triple
T32014849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayor of Keçiören |
E817506
|
entity |
| Predicate | officeNameInTurkish |
P198700
|
FINISHED |
| Object | Keçiören Belediye Başkanı |
—
|
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: Keçiören Belediye Başkanı | Statement: [Mayor of Keçiören, officeNameInTurkish, Keçiören Belediye Başkanı]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeNameInTurkish Context triple: [Mayor of Keçiören, officeNameInTurkish, Keçiören Belediye Başkanı]
-
A.
officeNameInArabic
Indicates the name of an office expressed in the Arabic language.
-
B.
officeNameInPortuguese
Indicates the name or title of an office as expressed in the Portuguese language.
-
C.
officeName
Indicates the official name assigned to an office or workplace.
-
D.
officeNameInDutch
Indicates the Dutch-language name or title used for a particular office, position, or role.
-
E.
officeNameInNynorsk
Indicates the name of an office expressed in the Nynorsk written standard of the Norwegian language.
- 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_69f348f9e5d081908cc3f57c4942af52 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
| PDg | Predicate description generation | batch_69feff703fec8190ab7d0633e0cc5459 |
completed | May 9, 2026, 9:33 a.m. |
Created at: May 1, 2026, 12:16 a.m.