Triple
T4526879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konya Province |
E106200
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Ilgın
Ilgın is a town and district in Turkey’s Konya Province, known for its thermal springs and agricultural activities.
|
E449750
|
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: Ilgın | Statement: [Konya Province, hasDistrict, Ilgın]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ilgın Context triple: [Konya Province, hasDistrict, Ilgın]
-
A.
Kaymaklı
Kaymaklı is an ancient multi-level underground city in Turkey’s Cappadocia region, renowned for its extensive tunnels, living quarters, and historical use as a refuge.
-
B.
Selamlık
Selamlık is the section of an Ottoman palace traditionally reserved for men, official ceremonies, and state affairs.
-
C.
Kanık
Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
-
D.
Nallıhan
Nallıhan is a district and town in Turkey known for its natural landscapes, including colorful rock formations and rich birdlife, located within Ankara Province.
-
E.
Oğuzeli
Oğuzeli is a town and district in Gaziantep Province in southeastern Turkey, known for its proximity to Gaziantep Oğuzeli International Airport and its role in the region’s agricultural and local trade activities.
- 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: Ilgın Triple: [Konya Province, hasDistrict, Ilgın]
Generated description
Ilgın is a town and district in Turkey’s Konya Province, known for its thermal springs and agricultural activities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ilgın Target entity description: Ilgın is a town and district in Turkey’s Konya Province, known for its thermal springs and agricultural activities.
-
A.
Kaymaklı
Kaymaklı is an ancient multi-level underground city in Turkey’s Cappadocia region, renowned for its extensive tunnels, living quarters, and historical use as a refuge.
-
B.
Selamlık
Selamlık is the section of an Ottoman palace traditionally reserved for men, official ceremonies, and state affairs.
-
C.
Kanık
Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
-
D.
Nallıhan
Nallıhan is a district and town in Turkey known for its natural landscapes, including colorful rock formations and rich birdlife, located within Ankara Province.
-
E.
Oğuzeli
Oğuzeli is a town and district in Gaziantep Province in southeastern Turkey, known for its proximity to Gaziantep Oğuzeli International Airport and its role in the region’s agricultural and local trade activities.
- 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_69bda4577d0c8190a88cdf4523446329 |
completed | March 20, 2026, 7:47 p.m. |
| NEDg | Description generation | batch_69bda8367b988190bd6859581ba9a38e |
completed | March 20, 2026, 8:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bda8b4d064819083de58ee18458fa8 |
completed | March 20, 2026, 8:06 p.m. |
Created at: March 20, 2026, 1:03 p.m.