Triple
T15776443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tashkent Region |
E382503
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Angren
Angren is an industrial city in eastern Uzbekistan known for its coal mining and energy production.
|
E1176316
|
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: Angren | Statement: [Tashkent Region, containsCity, Angren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angren Context triple: [Tashkent Region, containsCity, Angren]
-
A.
Targovishte
Targovishte is a town in northeastern Bulgaria known as an administrative and economic center with historical roots dating back to the Ottoman period.
-
B.
Monastir
Monastir, known today as Bitola in North Macedonia, is a historic Balkan city that played a significant strategic role during World War I.
-
C.
Monastir
Monastir is a small town and municipality in southern Sardinia, Italy, known for its agricultural activities and proximity to the regional capital Cagliari.
-
D.
Monastir
Monastir is a coastal city in central-eastern Tunisia, known as a historic port and the birthplace and burial place of the country’s first president, Habib Bourguiba.
-
E.
Dojran
Dojran is a town in southeastern North Macedonia near the Greek border, known for its proximity to Lake Dojran and its historical significance dating back to ancient and Ottoman times.
- 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: Angren Triple: [Tashkent Region, containsCity, Angren]
Generated description
Angren is an industrial city in eastern Uzbekistan known for its coal mining and energy production.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Angren Target entity description: Angren is an industrial city in eastern Uzbekistan known for its coal mining and energy production.
-
A.
Targovishte
Targovishte is a town in northeastern Bulgaria known as an administrative and economic center with historical roots dating back to the Ottoman period.
-
B.
Monastir
Monastir, known today as Bitola in North Macedonia, is a historic Balkan city that played a significant strategic role during World War I.
-
C.
Monastir
Monastir is a small town and municipality in southern Sardinia, Italy, known for its agricultural activities and proximity to the regional capital Cagliari.
-
D.
Monastir
Monastir is a coastal city in central-eastern Tunisia, known as a historic port and the birthplace and burial place of the country’s first president, Habib Bourguiba.
-
E.
Dojran
Dojran is a town in southeastern North Macedonia near the Greek border, known for its proximity to Lake Dojran and its historical significance dating back to ancient and Ottoman times.
- 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.