Triple
T8871287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherkessk |
E211161
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object |
Batalpashinskaya
Batalpashinskaya was the former name of the city now known as Cherkessk, a regional center in the North Caucasus of Russia.
|
E763439
|
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: Batalpashinskaya | Statement: [Cherkessk, formerName, Batalpashinskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Batalpashinskaya Context triple: [Cherkessk, formerName, Batalpashinskaya]
-
A.
Borovitskaya
Borovitskaya is a Moscow Metro station located in the city center, providing key interchange access between several central lines.
-
B.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
C.
Bogdanovka
Bogdanovka is a village in Ukraine known as the site of a World War II massacre of Jews and now commemorated as a Holocaust memorial location.
-
D.
Krasnokamensk–Bichigt
Krasnokamensk–Bichigt is an international border crossing point linking Russia and Mongolia, facilitating road and trade traffic between the two countries.
-
E.
Chertanovskaya
Chertanovskaya is a Moscow Metro station serving the Chertanovo district in the city’s south.
- 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: Batalpashinskaya Triple: [Cherkessk, formerName, Batalpashinskaya]
Generated description
Batalpashinskaya was the former name of the city now known as Cherkessk, a regional center in the North Caucasus of Russia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Batalpashinskaya Target entity description: Batalpashinskaya was the former name of the city now known as Cherkessk, a regional center in the North Caucasus of Russia.
-
A.
Borovitskaya
Borovitskaya is a Moscow Metro station located in the city center, providing key interchange access between several central lines.
-
B.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
C.
Bogdanovka
Bogdanovka is a village in Ukraine known as the site of a World War II massacre of Jews and now commemorated as a Holocaust memorial location.
-
D.
Krasnokamensk–Bichigt
Krasnokamensk–Bichigt is an international border crossing point linking Russia and Mongolia, facilitating road and trade traffic between the two countries.
-
E.
Chertanovskaya
Chertanovskaya is a Moscow Metro station serving the Chertanovo district in the city’s south.
- 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_69ca838d3c7c8190a849566d5afd2b11 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6126d2f88190979ab25772ee657c |
completed | April 1, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0ea9f5c8190b5c32fb1fefdc68b |
completed | April 3, 2026, 11:13 a.m. |
| NEDg | Description generation | batch_69cfa191d7d0819085a6b9bf7fa56067 |
completed | April 3, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfa28b1d1c8190ab4a10ba8fa7259d |
completed | April 3, 2026, 11:20 a.m. |
Created at: March 30, 2026, 6:51 p.m.