Triple
T13556639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gölbaşı Campus |
E323791
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Gölbaşı |
E330375
|
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: Gölbaşı | Statement: [Gölbaşı Campus, district, Gölbaşı]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gölbaşı Context triple: [Gölbaşı Campus, district, Gölbaşı]
-
A.
Gölbaşı
chosen
Gölbaşı is a district and suburban area of Ankara in central Turkey, known for its lakes, recreational areas, and proximity to the capital city.
-
B.
Aydıncık
Aydıncık is a coastal town and district in southern Turkey known for its Mediterranean shoreline and location within Mersin Province.
-
C.
Gölpazarı
Gölpazarı is a town and district in northwestern Turkey known for its rural character and location within Bilecik Province.
-
D.
Gökçen
Gökçen is a Turkish surname most famously borne by Sabiha Gökçen, one of the world’s first female fighter pilots and an adopted daughter of Mustafa Kemal Atatürk.
-
E.
Doğanhisar
Doğanhisar is a rural district and town in central Turkey known for its agricultural economy and location within the Konya region.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaff3063c8190bd20149b3f7df352 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd54f5323c8190aa239bad461b0857 |
completed | May 8, 2026, 3:13 a.m. |
Created at: April 9, 2026, 9:47 p.m.