Triple
T18429440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eşrefoğlu Mosque |
E450224
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Beyşehir |
—
|
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: Beyşehir | Statement: [Eşrefoğlu Mosque, locatedIn, Beyşehir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beyşehir Context triple: [Eşrefoğlu Mosque, locatedIn, Beyşehir]
-
A.
Beyşehir
chosen
Beyşehir is a town and district in central Turkey known for its large freshwater lake, Lake Beyşehir, and its rich Seljuk-era architectural heritage.
-
B.
Havza
Havza is a district and town in northern Turkey known for its thermal springs and location within Samsun Province in the Black Sea region.
-
C.
Gölbaşı
Gölbaşı is a district and suburban area of Ankara in central Turkey, known for its lakes, recreational areas, and proximity to the capital city.
-
D.
Büyükerşen
Büyükerşen is a Turkish surname most prominently associated with Yılmaz Büyükerşen, a well-known academic and long-serving mayor of Eskişehir.
-
E.
Yakapınar
Yakapınar is a modern settlement in southern Turkey located near the site of the ancient city of Mopsuestia.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51b15e2e081908c96c5678ff4b941 |
completed | April 19, 2026, 6:12 p.m. |
Created at: April 10, 2026, 11:26 a.m.