Triple
T8206326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikhail Sholokhov |
E191696
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Veshenskaya
Veshenskaya is a rural Cossack stanitsa in Russia’s Rostov Oblast, best known as the home village of Nobel Prize–winning writer Mikhail Sholokhov and the setting for much of his work.
|
E719416
|
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: Veshenskaya | Statement: [Mikhail Sholokhov, placeOfBirth, Veshenskaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veshenskaya Context triple: [Mikhail Sholokhov, placeOfBirth, Veshenskaya]
-
A.
Dobryninskaya
Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
-
B.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
C.
Paveletskaya
Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
-
D.
Savyolovskaya
Savyolovskaya is a Moscow Metro station on the Big Circle Line, serving as part of the city’s modern orbital rapid transit network.
-
E.
Savyolovskaya
Savyolovskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the northern part of the city.
- 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: Veshenskaya Triple: [Mikhail Sholokhov, placeOfBirth, Veshenskaya]
Generated description
Veshenskaya is a rural Cossack stanitsa in Russia’s Rostov Oblast, best known as the home village of Nobel Prize–winning writer Mikhail Sholokhov and the setting for much of his work.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Veshenskaya Target entity description: Veshenskaya is a rural Cossack stanitsa in Russia’s Rostov Oblast, best known as the home village of Nobel Prize–winning writer Mikhail Sholokhov and the setting for much of his work.
-
A.
Dobryninskaya
Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
-
B.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
C.
Paveletskaya
Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
-
D.
Savyolovskaya
Savyolovskaya is a Moscow Metro station on the Big Circle Line, serving as part of the city’s modern orbital rapid transit network.
-
E.
Savyolovskaya
Savyolovskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the northern part of the city.
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb726b520081908ce4a03bd14dfcdf |
completed | March 31, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccedd27bc08190a8109217069a8978 |
completed | April 1, 2026, 10:05 a.m. |
| NEDg | Description generation | batch_69ccf1b818588190936f96d53bf08c2b |
completed | April 1, 2026, 10:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd05c2059081908bd04ee4722f9aad |
completed | April 1, 2026, 11:47 a.m. |
Created at: March 30, 2026, 5:43 p.m.