Triple
T17281379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belek |
E419535
|
entity |
| Predicate | administrativeDivision |
P747
|
FINISHED |
| Object | Serik |
E425998
|
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: Serik | Statement: [Belek, administrativeDivision, Serik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serik Context triple: [Belek, administrativeDivision, Serik]
-
A.
Serik
chosen
Serik is a town and district in Turkey’s Antalya Province, known as a gateway to nearby ancient sites and Mediterranean coastal resorts.
-
B.
Kargilik
Kargilik is a historic oasis town in southwestern Xinjiang, China, situated along the ancient Silk Road and traditionally inhabited by Uyghur communities.
-
C.
Sıhhiye
Sıhhiye is a central district and major transportation hub in Ankara, Turkey, known for its government buildings, hospitals, and busy urban thoroughfares.
-
D.
Siverek
Siverek is a large district and town in southeastern Turkey known for its predominantly Kurdish population and its location within the historical region of Upper Mesopotamia.
-
E.
Serdivan
Serdivan is a rapidly developing district and suburban area of the city of Sakarya in northwestern Turkey, known for its residential neighborhoods, university presence, and growing commercial centers.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e4332a4c008190b44f4145d0e94a21 |
completed | April 19, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0179535ae08190ac0137d0f8741919 |
completed | May 11, 2026, 6:38 a.m. |
Created at: April 10, 2026, 5:40 a.m.