Triple
T9815421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakarya Province |
E238390
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Adapazarı |
E445168
|
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: Adapazarı | Statement: [Sakarya Province, largestCity, Adapazarı]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adapazarı Context triple: [Sakarya Province, largestCity, Adapazarı]
-
A.
Adapazarı
chosen
Adapazarı is a city in northwestern Turkey that serves as the administrative center of Sakarya Province and is known for its agricultural production and regional commerce.
-
B.
Eskişehir
Eskişehir is a major university and industrial city in northwestern Turkey, known for its vibrant student life, modern urban design, and rich cultural heritage.
-
C.
Medinaceli
Medinaceli is a historic town in the province of Soria, Spain, known for its well-preserved medieval architecture and Roman heritage.
-
D.
Karabük
Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
-
E.
Trabzon
Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f341648190bf8343e1124085cb |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cb4b301c8190907d5e31ca7bb228 |
completed | April 5, 2026, 8:51 p.m. |
Created at: March 30, 2026, 8:30 p.m.