Triple
T4065044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konya High-Speed Train Station |
E86304
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Polatlı |
E315503
|
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: Polatlı | Statement: [Konya High-Speed Train Station, connectsTo, Polatlı]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Polatlı Context triple: [Konya High-Speed Train Station, connectsTo, Polatlı]
-
A.
Polatlı
chosen
Polatlı is a town and district in central Turkey known for its agricultural economy and its proximity to the historic Battle of Sakarya site.
-
B.
Gökalp
Gökalp is a Turkish surname most prominently associated with Ziya Gökalp, an influential early 20th-century sociologist, writer, and ideologue of Turkish nationalism.
-
C.
Kaymaklı
Kaymaklı is an ancient multi-level underground city in Turkey’s Cappadocia region, renowned for its extensive tunnels, living quarters, and historical use as a refuge.
-
D.
Havaş
Havaş is a Turkish ground handling and airport services company operating at numerous airports domestically and internationally.
-
E.
Akyurt
Akyurt is a district and rapidly developing suburban area of Ankara in central Turkey, known for its industrial zones and proximity to the capital’s airport.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf44c888190b5746d93e9f8e3a3 |
completed | March 9, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b562ae949c819092affaaca97c16d1 |
completed | March 14, 2026, 1:29 p.m. |
Created at: March 9, 2026, 3:38 p.m.