Triple
T7840480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | İzmir Province |
E181790
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Bayındır
Bayındır is a town and district in western Turkey known for its agricultural production and location within İzmir Province.
|
E714821
|
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: Bayındır | Statement: [İzmir Province, contains, Bayındır]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bayındır Context triple: [İzmir Province, contains, Bayındır]
-
A.
Arnavutköy
Arnavutköy is a district on the European side of Istanbul, Turkey, known for its rapidly developing urban areas and hosting the city’s main international airport.
-
B.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
C.
Körfez
Körfez is a coastal industrial city and district in Turkey’s Kocaeli Province, located along the Gulf of İzmit in the Marmara region.
-
D.
Florya
Florya is a coastal neighborhood in Istanbul, Turkey, known for its residential areas, seaside promenade, and recreational facilities.
-
E.
Kanık
Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
- 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: Bayındır Triple: [İzmir Province, contains, Bayındır]
Generated description
Bayındır is a town and district in western Turkey known for its agricultural production and location within İzmir Province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bayındır Target entity description: Bayındır is a town and district in western Turkey known for its agricultural production and location within İzmir Province.
-
A.
Arnavutköy
Arnavutköy is a district on the European side of Istanbul, Turkey, known for its rapidly developing urban areas and hosting the city’s main international airport.
-
B.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
C.
Körfez
Körfez is a coastal industrial city and district in Turkey’s Kocaeli Province, located along the Gulf of İzmit in the Marmara region.
-
D.
Florya
Florya is a coastal neighborhood in Istanbul, Turkey, known for its residential areas, seaside promenade, and recreational facilities.
-
E.
Kanık
Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c589748190b34d0911d373e194 |
completed | March 31, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbda1033c819088372a46a74c575d |
completed | April 1, 2026, 6:39 a.m. |
| NEDg | Description generation | batch_69ccc24a39f88190995f076d1a7ec3e7 |
completed | April 1, 2026, 6:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ccc37f0ca88190b4e077f23dbbe6f8 |
completed | April 1, 2026, 7:04 a.m. |
Created at: March 30, 2026, 4:47 p.m.