Triple
T11846564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rybinsk |
E281792
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object |
Shcherbakov
Shcherbakov was a former Soviet-era name of the Russian city now known as Rybinsk.
|
E954191
|
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: Shcherbakov | Statement: [Rybinsk, historicalName, Shcherbakov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shcherbakov Context triple: [Rybinsk, historicalName, Shcherbakov]
-
A.
Shchusev
Shchusev is a Russian surname most notably associated with Alexey Shchusev, a prominent Soviet architect known for designing Lenin's Mausoleum in Moscow.
-
B.
Yuryatin
Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
-
C.
Khokhlov
Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
-
D.
Chebutykin
Chebutykin is the aging, disillusioned army doctor whose cynicism and emotional detachment embody the themes of lost hope and stagnation in Anton Chekhov’s play "Three Sisters."
-
E.
Shchekochikhin
Shchekochikhin is a Russian surname most notably associated with Yuri Shchekochikhin, a prominent investigative journalist and politician.
- 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: Shcherbakov Triple: [Rybinsk, historicalName, Shcherbakov]
Generated description
Shcherbakov was a former Soviet-era name of the Russian city now known as Rybinsk.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shcherbakov Target entity description: Shcherbakov was a former Soviet-era name of the Russian city now known as Rybinsk.
-
A.
Shchusev
Shchusev is a Russian surname most notably associated with Alexey Shchusev, a prominent Soviet architect known for designing Lenin's Mausoleum in Moscow.
-
B.
Yuryatin
Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
-
C.
Khokhlov
Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
-
D.
Chebutykin
Chebutykin is the aging, disillusioned army doctor whose cynicism and emotional detachment embody the themes of lost hope and stagnation in Anton Chekhov’s play "Three Sisters."
-
E.
Shchekochikhin
Shchekochikhin is a Russian surname most notably associated with Yuri Shchekochikhin, a prominent investigative journalist and politician.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65b5ff08190bb58361f6a6acdca |
completed | April 10, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f43fb078148190bdd7f36c6b292670 |
completed | May 1, 2026, 5:52 a.m. |
| NEDg | Description generation | batch_69f448f506a48190a0f1b89ad570fad5 |
completed | May 1, 2026, 6:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f44ad185cc8190893cf663cfed6980 |
completed | May 1, 2026, 6:40 a.m. |
Created at: April 8, 2026, 9:43 p.m.