Triple
T4526888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konya Province |
E106200
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Yunak
Yunak is a rural district and town in Turkey known for its agricultural economy and location within the Central Anatolia region.
|
E449756
|
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: Yunak | Statement: [Konya Province, hasDistrict, Yunak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yunak Context triple: [Konya Province, hasDistrict, Yunak]
-
A.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
B.
Khashuri
Khashuri is a town in central Georgia that serves as an important regional transport hub and gateway between eastern and western parts of the country.
-
C.
Yakutiye
Yakutiye is a central district and municipality of the city of Erzurum in eastern Turkey, serving as one of its main administrative and urban areas.
-
D.
Nokhchi
Nokhchi is the endonym used by the Chechen people to refer to themselves as an ethnic group indigenous to the North Caucasus region.
-
E.
Bulganin
Bulganin is the surname of Nikolai Bulganin, a prominent Soviet politician who served as Premier of the Soviet Union during the 1950s.
- 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: Yunak Triple: [Konya Province, hasDistrict, Yunak]
Generated description
Yunak is a rural district and town in Turkey known for its agricultural economy and location within the Central Anatolia region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yunak Target entity description: Yunak is a rural district and town in Turkey known for its agricultural economy and location within the Central Anatolia region.
-
A.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
B.
Khashuri
Khashuri is a town in central Georgia that serves as an important regional transport hub and gateway between eastern and western parts of the country.
-
C.
Yakutiye
Yakutiye is a central district and municipality of the city of Erzurum in eastern Turkey, serving as one of its main administrative and urban areas.
-
D.
Nokhchi
Nokhchi is the endonym used by the Chechen people to refer to themselves as an ethnic group indigenous to the North Caucasus region.
-
E.
Bulganin
Bulganin is the surname of Nikolai Bulganin, a prominent Soviet politician who served as Premier of the Soviet Union during the 1950s.
- 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.