Triple
T4526883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konya Province |
E106200
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Karapınar
Karapınar is a district and town in central Turkey known for its arid landscape, sand dunes, and sinkholes within Konya Province.
|
E467944
|
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: Karapınar | Statement: [Konya Province, hasDistrict, Karapınar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karapınar Context triple: [Konya Province, hasDistrict, Karapınar]
-
A.
Toprakkale
Toprakkale is an ancient fortress and archaeological site in eastern Turkey that served as a significant center of the Iron Age Kingdom of Urartu.
-
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.
Karabük
Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
-
D.
Menemen
Menemen is a district and town in İzmir Province, Turkey, known for its agricultural production and as part of the greater İzmir metropolitan area.
-
E.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
- 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: Karapınar Triple: [Konya Province, hasDistrict, Karapınar]
Generated description
Karapınar is a district and town in central Turkey known for its arid landscape, sand dunes, and sinkholes within Konya Province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karapınar Target entity description: Karapınar is a district and town in central Turkey known for its arid landscape, sand dunes, and sinkholes within Konya Province.
-
A.
Toprakkale
Toprakkale is an ancient fortress and archaeological site in eastern Turkey that served as a significant center of the Iron Age Kingdom of Urartu.
-
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.
Karabük
Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
-
D.
Menemen
Menemen is a district and town in İzmir Province, Turkey, known for its agricultural production and as part of the greater İzmir metropolitan area.
-
E.
Karaköy
Karaköy is a historic waterfront neighborhood in Istanbul known for its bustling port, cafes, and mix of traditional and modern urban life.
- 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_69bd43f3d6e08190a91824f833d51bbe |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57760f4481908f69ce82be63d7f8 |
completed | March 20, 2026, 2:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be397d7358819086fa3851318973ea |
completed | March 21, 2026, 6:23 a.m. |
| NEDg | Description generation | batch_69be3d05281481909a74ffb38fb5eb31 |
completed | March 21, 2026, 6:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be3dc3ce048190a725ea4b8e8a1ad4 |
completed | March 21, 2026, 6:42 a.m. |
Created at: March 20, 2026, 1:03 p.m.