Triple
T14387619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bryansk Oblast |
E356765
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Novozybkov
Novozybkov is a town in western Russia known as a local administrative and economic center near the borders with Belarus and Ukraine.
|
E1171045
|
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: Novozybkov | Statement: [Bryansk Oblast, hasCity, Novozybkov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Novozybkov Context triple: [Bryansk Oblast, hasCity, Novozybkov]
-
A.
Votkinsk
Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
-
B.
Zvenigorod
Zvenigorod is a historic town near Moscow, Russia, known for its ancient monasteries, traditional Russian architecture, and role as a cultural and spiritual center.
-
C.
Solikamsk
Solikamsk is a historic industrial city in Russia known for its major salt and chemical industries and its location in the northern part of Perm Krai.
-
D.
Priozersk
Priozersk is a small town in northwestern Russia known for its historic fortress Korela and its location on the shores of Lake Ladoga.
-
E.
Kovrov
Kovrov is an industrial city in western Russia known for its machine-building and arms manufacturing industries.
- 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: Novozybkov Triple: [Bryansk Oblast, hasCity, Novozybkov]
Generated description
Novozybkov is a town in western Russia known as a local administrative and economic center near the borders with Belarus and Ukraine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Novozybkov Target entity description: Novozybkov is a town in western Russia known as a local administrative and economic center near the borders with Belarus and Ukraine.
-
A.
Votkinsk
Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
-
B.
Zvenigorod
Zvenigorod is a historic town near Moscow, Russia, known for its ancient monasteries, traditional Russian architecture, and role as a cultural and spiritual center.
-
C.
Solikamsk
Solikamsk is a historic industrial city in Russia known for its major salt and chemical industries and its location in the northern part of Perm Krai.
-
D.
Priozersk
Priozersk is a small town in northwestern Russia known for its historic fortress Korela and its location on the shores of Lake Ladoga.
-
E.
Kovrov
Kovrov is an industrial city in western Russia known for its machine-building and arms manufacturing industries.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90283b9c8190b50d30ad58bfe085 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ebeb5ec8190afef40d87c74a8a0 |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff702588908190a1b1dd1fd6a972f9 |
completed | May 9, 2026, 5:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff70f97eec8190a1f5affdad31f2b2 |
completed | May 9, 2026, 5:38 p.m. |
Created at: April 10, 2026, 1:16 a.m.