Triple
T15776448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tashkent Region |
E382503
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Ohangaron
Ohangaron is a city in eastern Uzbekistan that serves as an industrial and agricultural center within the Tashkent Region.
|
E1176320
|
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: Ohangaron | Statement: [Tashkent Region, containsCity, Ohangaron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ohangaron Context triple: [Tashkent Region, containsCity, Ohangaron]
-
A.
Zungeru
Zungeru is a historic town in north-central Nigeria, known as a former colonial administrative center and the birthplace of Nigeria’s first president, Nnamdi Azikiwe.
-
B.
Ahangama
Ahangama is a coastal town in southern Sri Lanka known for its beaches, surfing spots, and traditional stilt fishermen.
-
C.
Karonga
Karonga is a town in northern Malawi located on the shores of Lake Malawi, known as a regional transport hub and archaeological site.
-
D.
Githunguri
Githunguri is a town in Kenya known for its agricultural activities, particularly dairy and coffee farming, within Kiambu County.
-
E.
Chirawa
Chirawa is a town in the Jhunjhunu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani culture.
- 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: Ohangaron Triple: [Tashkent Region, containsCity, Ohangaron]
Generated description
Ohangaron is a city in eastern Uzbekistan that serves as an industrial and agricultural center within the Tashkent Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ohangaron Target entity description: Ohangaron is a city in eastern Uzbekistan that serves as an industrial and agricultural center within the Tashkent Region.
-
A.
Zungeru
Zungeru is a historic town in north-central Nigeria, known as a former colonial administrative center and the birthplace of Nigeria’s first president, Nnamdi Azikiwe.
-
B.
Ahangama
Ahangama is a coastal town in southern Sri Lanka known for its beaches, surfing spots, and traditional stilt fishermen.
-
C.
Karonga
Karonga is a town in northern Malawi located on the shores of Lake Malawi, known as a regional transport hub and archaeological site.
-
D.
Githunguri
Githunguri is a town in Kenya known for its agricultural activities, particularly dairy and coffee farming, within Kiambu County.
-
E.
Chirawa
Chirawa is a town in the Jhunjhunu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani culture.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05199cd8881909462462cec34d35a |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff909b467c819097ee87f51d2001da |
completed | May 9, 2026, 7:52 p.m. |
| NEDg | Description generation | batch_69ff9277dc2881908fe0cd70e3d61f3f |
completed | May 9, 2026, 8 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff93745f508190927b79a5debead12 |
completed | May 9, 2026, 8:05 p.m. |
Created at: April 10, 2026, 4:47 a.m.