Triple
T7141735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tekirdağ Province |
E166458
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Çerkezköy
Çerkezköy is an industrial and residential town in northwestern Turkey, located in Tekirdağ Province within the Thrace region.
|
E646661
|
NE FINISHED |
How this triple was built (4 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: Çerkezköy | Statement: [Tekirdağ Province, hasCity, Çerkezköy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Çerkezköy Context triple: [Tekirdağ Province, hasCity, Çerkezköy]
-
A.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
-
B.
Şirinköy
Şirinköy is a village located on Gökçeada, Turkey’s largest Aegean island in the Çanakkale Province.
-
C.
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.
-
D.
Keçiören
Keçiören is a densely populated metropolitan district and municipality of Ankara, known as one of the capital city’s major residential and commercial areas.
-
E.
Poyrazköy
Poyrazköy is a coastal neighborhood on the Asian side of Istanbul, Turkey, situated at the northern entrance of the Bosphorus Strait.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Çerkezköy Triple: [Tekirdağ Province, hasCity, Çerkezköy]
Generated description
Çerkezköy is an industrial and residential town in northwestern Turkey, located in Tekirdağ Province within the Thrace region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Çerkezköy Target entity description: Çerkezköy is an industrial and residential town in northwestern Turkey, located in Tekirdağ Province within the Thrace region.
-
A.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
-
B.
Şirinköy
Şirinköy is a village located on Gökçeada, Turkey’s largest Aegean island in the Çanakkale Province.
-
C.
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.
-
D.
Keçiören
Keçiören is a densely populated metropolitan district and municipality of Ankara, known as one of the capital city’s major residential and commercial areas.
-
E.
Poyrazköy
Poyrazköy is a coastal neighborhood on the Asian side of Istanbul, Turkey, situated at the northern entrance of the Bosphorus Strait.
- F. None of above. chosen
Provenance (5 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e778875c8190a5202d3efe5a842d |
completed | March 27, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b8e72bf081909bb63a4b6f2613df |
completed | March 28, 2026, 11:17 a.m. |
| NEDg | Description generation | batch_69c7b98e36548190827226942c41a0f0 |
completed | March 28, 2026, 11:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ba07b138819087b4352a07c37a71 |
completed | March 28, 2026, 11:22 a.m. |
Created at: March 27, 2026, 2:45 p.m.