Triple
T20577108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Shcherbatsky |
E505246
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Shcherbatsky
Shcherbatsky is the aristocratic Russian family name of a prominent noble household featured in Leo Tolstoy’s novel "Anna Karenina."
|
E1438413
|
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: Shcherbatsky | Statement: [Prince Shcherbatsky, familyName, Shcherbatsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shcherbatsky Context triple: [Prince Shcherbatsky, familyName, Shcherbatsky]
-
A.
Kastrychnitskaya
Kastrychnitskaya is a central Minsk Metro station known for serving the heart of Belarus’s capital near key administrative and cultural landmarks.
-
B.
Grushevskaya
Grushevskaya is a Russian-language surname of Slavic origin.
-
C.
Skhodnenskaya
Skhodnenskaya is a Moscow Metro station on the Tagansko-Krasnopresnenskaya Line serving the northwestern part of the city.
-
D.
Yezernitsky
Yezernitsky is a Jewish surname most notably associated with Yitzhak Shamir, the former Prime Minister of Israel, who was born Yitzhak Yezernitsky.
-
E.
Shchusev
Shchusev is a Russian surname most notably associated with Alexey Shchusev, a prominent Soviet architect known for designing Lenin's Mausoleum in Moscow.
- 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: Shcherbatsky Triple: [Prince Shcherbatsky, familyName, Shcherbatsky]
Generated description
Shcherbatsky is the aristocratic Russian family name of a prominent noble household featured in Leo Tolstoy’s novel "Anna Karenina."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shcherbatsky Target entity description: Shcherbatsky is the aristocratic Russian family name of a prominent noble household featured in Leo Tolstoy’s novel "Anna Karenina."
-
A.
Kastrychnitskaya
Kastrychnitskaya is a central Minsk Metro station known for serving the heart of Belarus’s capital near key administrative and cultural landmarks.
-
B.
Grushevskaya
Grushevskaya is a Russian-language surname of Slavic origin.
-
C.
Skhodnenskaya
Skhodnenskaya is a Moscow Metro station on the Tagansko-Krasnopresnenskaya Line serving the northwestern part of the city.
-
D.
Yezernitsky
Yezernitsky is a Jewish surname most notably associated with Yitzhak Shamir, the former Prime Minister of Israel, who was born Yitzhak Yezernitsky.
-
E.
Shchusev
Shchusev is a Russian surname most notably associated with Alexey Shchusev, a prominent Soviet architect known for designing Lenin's Mausoleum in Moscow.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a90bbcfc81909ca4cab8038c634b |
completed | April 20, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08ace8a1d881908a8b178308c7b202 |
completed | May 16, 2026, 5:44 p.m. |
| NEDg | Description generation | batch_6a08ad96b2a081908d32e335c5265eec |
completed | May 16, 2026, 5:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08ae19eca08190ada48b48105be62d |
completed | May 16, 2026, 5:49 p.m. |
Created at: April 16, 2026, 11:39 a.m.