Triple
T17700450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LTAN |
E441283
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Konya, Turkey |
—
|
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: Konya, Turkey | Statement: [LTAN, location, Konya, Turkey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Konya, Turkey Context triple: [LTAN, location, Konya, Turkey]
-
A.
Konya
chosen
Konya is a major city in central Anatolia known for its rich Seljuk heritage and as the home of the Sufi mystic Rumi and the Whirling Dervishes.
-
B.
Kayseri
Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
-
C.
Konya Province
Konya Province is a large administrative region in central Turkey known for its historical significance, agricultural productivity, and the city of Konya as its cultural and economic center.
-
D.
Karacabey
Karacabey is a town and district in northwestern Turkey known for its agriculture and proximity to both the Marmara Sea and the city of Bursa.
-
E.
Sakarya, Turkey
Sakarya, Turkey is an industrial and agricultural province in northwestern Turkey, known for its automotive manufacturing plants and strategic location near Istanbul.
- 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4715ae1fc81908438a1bba970c6ec |
completed | April 19, 2026, 6:08 a.m. |
Created at: April 10, 2026, 10:04 a.m.