Triple
T1946730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sokolnicheskaya Line |
E42070
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Komsomolskaya station
Komsomolskaya station is a prominent Moscow Metro station known for its grand Stalinist architecture and location beneath Komsomolskaya Square, a major railway hub.
|
E306617
|
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: Komsomolskaya station | Statement: [Sokolnicheskaya Line, hasStation, Komsomolskaya station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Komsomolskaya station Context triple: [Sokolnicheskaya Line, hasStation, Komsomolskaya station]
-
A.
Komsomolskaya station
Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
B.
Krasnoselskaya station
Krasnoselskaya station is a Moscow Metro station known for its early Soviet-era architecture and location on the system’s first metro line.
-
C.
Kachinskaya station
Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
D.
Dzerzhinskaya station
Dzerzhinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
E.
Traktorozavodskaya station
Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district 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: Komsomolskaya station Triple: [Sokolnicheskaya Line, hasStation, Komsomolskaya station]
Generated description
Komsomolskaya station is a prominent Moscow Metro station known for its grand Stalinist architecture and location beneath Komsomolskaya Square, a major railway hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Komsomolskaya station Target entity description: Komsomolskaya station is a prominent Moscow Metro station known for its grand Stalinist architecture and location beneath Komsomolskaya Square, a major railway hub.
-
A.
Komsomolskaya station
Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
B.
Krasnoselskaya station
Krasnoselskaya station is a Moscow Metro station known for its early Soviet-era architecture and location on the system’s first metro line.
-
C.
Kachinskaya station
Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
D.
Dzerzhinskaya station
Dzerzhinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
E.
Traktorozavodskaya station
Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb32ebae881908f7541301f0198ae |
completed | March 7, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01cf667bc81909d1de1542d53076a |
completed | March 10, 2026, 1:30 p.m. |
| NEDg | Description generation | batch_69b022df23ec81909b4db2bb3fa2a76f |
completed | March 10, 2026, 1:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b02394cf6c8190a4ac013f46d89806 |
completed | March 10, 2026, 1:58 p.m. |
Created at: March 4, 2026, 7:36 p.m.