Triple
T15806462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nazilli |
E383227
|
entity |
| Predicate | hasNeighbouringDistrict |
P17964
|
FINISHED |
| Object | Buharkent |
E1088161
|
NE 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: Buharkent | Statement: [Nazilli, hasNeighbouringDistrict, Buharkent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buharkent Context triple: [Nazilli, hasNeighbouringDistrict, Buharkent]
-
A.
Buharkent
chosen
Buharkent is a small district and town in western Turkey known for its geothermal resources and agricultural production within Aydın Province.
-
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.
Gürbulak
Gürbulak is a Turkish border village and crossing point on the frontier with Iran, serving as a key gateway between the two countries.
-
D.
Batu City
Batu City is a highland tourist city in East Java, Indonesia, known for its cool climate, mountain scenery, and numerous recreational attractions.
-
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 (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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52751348190964e82463ce9dd20 |
completed | April 16, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb038dac881909ede37fa7766a249 |
completed | May 9, 2026, 10:07 p.m. |
Created at: April 10, 2026, 4:48 a.m.