Triple
T10277921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bilecik Province |
E241016
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Yenipazar
Yenipazar is a small town and district in northwestern Turkey known for its rural character and traditional Anatolian lifestyle.
|
E862745
|
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: Yenipazar | Statement: [Bilecik Province, contains, Yenipazar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yenipazar Context triple: [Bilecik Province, contains, Yenipazar]
-
A.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
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.
Kabataş
Kabataş is a coastal neighborhood in Istanbul, Turkey, known as a major transportation hub with ferry, tram, and funicular connections along the Bosphorus.
-
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.
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.
- 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: Yenipazar Triple: [Bilecik Province, contains, Yenipazar]
Generated description
Yenipazar is a small town and district in northwestern Turkey known for its rural character and traditional Anatolian lifestyle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yenipazar Target entity description: Yenipazar is a small town and district in northwestern Turkey known for its rural character and traditional Anatolian lifestyle.
-
A.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
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.
Kabataş
Kabataş is a coastal neighborhood in Istanbul, Turkey, known as a major transportation hub with ferry, tram, and funicular connections along the Bosphorus.
-
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.
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.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d29f0cf08190a2c5e7523d5c731e |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e40205c8190a4788e1db1f149d2 |
completed | April 10, 2026, 4:36 a.m. |
| NEDg | Description generation | batch_69d8837e70508190b03e8983b2617eac |
completed | April 10, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d889cc40648190a1d80b955e676ea5 |
completed | April 10, 2026, 5:25 a.m. |
Created at: April 6, 2026, 11:37 a.m.