Triple
T5491990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asian Turkey |
E123721
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Belek |
E419535
|
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: Belek | Statement: [Asian Turkey, containsCity, Belek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belek Context triple: [Asian Turkey, containsCity, Belek]
-
A.
Belek
chosen
Belek is a popular resort town on Turkey’s Mediterranean coast, known for its beaches, luxury hotels, and championship golf courses.
-
B.
Kanık
Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
-
C.
Gölcük
Gölcük is a coastal town and district in northwestern Turkey, situated on the Gulf of İzmit and known for its naval base and shipyard.
-
D.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
-
E.
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.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9280403c8190baaa3f7923449a37 |
completed | March 20, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf77b725988190b578ca5b3417d980 |
completed | March 22, 2026, 5:01 a.m. |
Created at: March 20, 2026, 2:10 p.m.