Triple
T12665190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsvetnoy Bulvar |
E302532
|
entity |
| Predicate | hasTransferTo |
P17241
|
FINISHED |
| Object |
Trubnaya
Trubnaya is a Moscow Metro station located in the city center, known for its deep-level construction and transfer connection with Tsvetnoy Bulvar station.
|
E995807
|
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: Trubnaya | Statement: [Tsvetnoy Bulvar, hasTransferTo, Trubnaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trubnaya Context triple: [Tsvetnoy Bulvar, hasTransferTo, Trubnaya]
-
A.
Tulskaya
Tulskaya is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Tulskaya Square area in southern Moscow.
-
B.
Chertanovskaya
Chertanovskaya is a Moscow Metro station serving the Chertanovo district in the city’s south.
-
C.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
D.
Rechitsa
Rechitsa is a historic town in southeastern Belarus, situated on the Dnieper River and known as one of the country’s oldest settlements.
-
E.
Semyonovskaya
Semyonovskaya is a station on the Moscow Metro, serving the Sokolnicheskaya Line in the eastern part of 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: Trubnaya Triple: [Tsvetnoy Bulvar, hasTransferTo, Trubnaya]
Generated description
Trubnaya is a Moscow Metro station located in the city center, known for its deep-level construction and transfer connection with Tsvetnoy Bulvar station.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trubnaya Target entity description: Trubnaya is a Moscow Metro station located in the city center, known for its deep-level construction and transfer connection with Tsvetnoy Bulvar station.
-
A.
Tulskaya
Tulskaya is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Tulskaya Square area in southern Moscow.
-
B.
Chertanovskaya
Chertanovskaya is a Moscow Metro station serving the Chertanovo district in the city’s south.
-
C.
Voykovskaya
Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
-
D.
Rechitsa
Rechitsa is a historic town in southeastern Belarus, situated on the Dnieper River and known as one of the country’s oldest settlements.
-
E.
Semyonovskaya
Semyonovskaya is a station on the Moscow Metro, serving the Sokolnicheskaya Line in the eastern part of 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617e030881908444743b8a7e0d75 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688a19148190b8d252d3706d2b05 |
completed | May 2, 2026, 9:11 p.m. |
| NEDg | Description generation | batch_69f669f69fe4819097dfc63780e8587e |
completed | May 2, 2026, 9:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f66b64dfe08190a7f9283dabd0e3c7 |
completed | May 2, 2026, 9:23 p.m. |
Created at: April 9, 2026, 5:19 p.m.