Triple
T13155251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaluzhsko–Rizhskaya Line |
E312566
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Novye Cheryomushki
Novye Cheryomushki is a Moscow Metro station serving the residential Cheryomushki district in southwestern Moscow.
|
E1024032
|
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: Novye Cheryomushki | Statement: [Kaluzhsko–Rizhskaya Line, hasStation, Novye Cheryomushki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Novye Cheryomushki Context triple: [Kaluzhsko–Rizhskaya Line, hasStation, Novye Cheryomushki]
-
A.
Mishenka
Mishenka is a Russian affectionate diminutive form of the male given name Mikhail.
-
B.
Taganana
Taganana is a historic coastal village on Tenerife in Spain’s Canary Islands, known for its dramatic cliffs, traditional architecture, and location within the Anaga mountain range.
-
C.
Shchyokino
Shchyokino is a town in Tula Oblast, Russia, known as a local industrial center and the administrative hub of its surrounding district.
-
D.
Yuriatin
Yuriatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Yuri Zhivago’s life and relationships.
-
E.
Molodyozhnaya
Molodyozhnaya is a Moscow Metro station serving the western part of the city on one of its main radial lines.
- 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: Novye Cheryomushki Triple: [Kaluzhsko–Rizhskaya Line, hasStation, Novye Cheryomushki]
Generated description
Novye Cheryomushki is a Moscow Metro station serving the residential Cheryomushki district in southwestern Moscow.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Novye Cheryomushki Target entity description: Novye Cheryomushki is a Moscow Metro station serving the residential Cheryomushki district in southwestern Moscow.
-
A.
Mishenka
Mishenka is a Russian affectionate diminutive form of the male given name Mikhail.
-
B.
Taganana
Taganana is a historic coastal village on Tenerife in Spain’s Canary Islands, known for its dramatic cliffs, traditional architecture, and location within the Anaga mountain range.
-
C.
Shchyokino
Shchyokino is a town in Tula Oblast, Russia, known as a local industrial center and the administrative hub of its surrounding district.
-
D.
Yuriatin
Yuriatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Yuri Zhivago’s life and relationships.
-
E.
Molodyozhnaya
Molodyozhnaya is a Moscow Metro station serving the western part of the city on one of its main radial lines.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c06ccb881909390df18e1a6f7ed |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaee8aa0819089994b85d56c7740 |
completed | May 3, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69f6ef102fb08190b8a9646e5b45155c |
completed | May 3, 2026, 6:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ef933f888190880e680f7f4c1c29 |
completed | May 3, 2026, 6:47 a.m. |
Created at: April 9, 2026, 9:12 p.m.