Triple
T23001452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakarya, Turkey |
E572641
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Kaynarca |
—
|
NE NERFINISHED |
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: Kaynarca | Statement: [Sakarya, Turkey, hasDistrict, Kaynarca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaynarca Context triple: [Sakarya, Turkey, hasDistrict, Kaynarca]
-
A.
Kaynarca
chosen
Kaynarca is a small town and district in northwestern Turkey, located within Sakarya Province and known for its rural character and agricultural activities.
-
B.
Orhangazi
Orhangazi is a town and district in northwestern Turkey known for its olive cultivation and location near Lake İznik in Bursa Province.
-
C.
Beştepe
Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
-
D.
Kajmakčalan
Kajmakčalan is a prominent peak on the Greece–North Macedonia border, historically known as a major World War I battlefield and part of the Mount Voras range.
-
E.
Büyükerşen
Büyükerşen is a Turkish surname most prominently associated with Yılmaz Büyükerşen, a well-known academic and long-serving mayor of Eskişehir.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18353d05481909abacb48a14ef21e |
completed | April 29, 2026, 4:04 a.m. |
Created at: April 17, 2026, 3:50 p.m.