Triple
T780696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uzbekistan |
E16489
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Namangan
Namangan is a major city in eastern Uzbekistan, known as an important cultural and economic center in the Fergana Valley.
|
E110802
|
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: Namangan | Statement: [Uzbekistan, hasCity, Namangan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namangan Context triple: [Uzbekistan, hasCity, Namangan]
-
A.
Andijan
Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
-
B.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
C.
Dashoguz
Dashoguz is a prominent city in northern Turkmenistan, serving as a regional administrative and economic center near the border with Uzbekistan.
-
D.
Shymkent
Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
-
E.
Khiva
Khiva is an ancient oasis city in western Uzbekistan renowned for its well-preserved walled old town, Itchan Kala, a UNESCO World Heritage Site.
- 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: Namangan Triple: [Uzbekistan, hasCity, Namangan]
Generated description
Namangan is a major city in eastern Uzbekistan, known as an important cultural and economic center in the Fergana Valley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Namangan Target entity description: Namangan is a major city in eastern Uzbekistan, known as an important cultural and economic center in the Fergana Valley.
-
A.
Andijan
Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
-
B.
Karaganda
Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
-
C.
Dashoguz
Dashoguz is a prominent city in northern Turkmenistan, serving as a regional administrative and economic center near the border with Uzbekistan.
-
D.
Shymkent
Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
-
E.
Khiva
Khiva is an ancient oasis city in western Uzbekistan renowned for its well-preserved walled old town, Itchan Kala, a UNESCO World Heritage Site.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a751ea3481908a622d5255249883 |
completed | March 1, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826c85e008190a7bba05607312192 |
completed | March 4, 2026, 12:34 p.m. |
| NEDg | Description generation | batch_69a83f42a2b0819093838d15a9406740 |
completed | March 4, 2026, 2:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a83fca462c8190aefe0f53fce8dfc6 |
completed | March 4, 2026, 2:20 p.m. |
Created at: March 1, 2026, 7:37 p.m.