Triple
T1847176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volgograd Metrotram |
E41308
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Kachinskaya station
Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
|
E247313
|
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: Kachinskaya station | Statement: [Volgograd Metrotram, hasStation, Kachinskaya station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kachinskaya station Context triple: [Volgograd Metrotram, hasStation, Kachinskaya station]
-
A.
Komsomolskaya station
Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
B.
Khimvolokno station
Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
C.
Dzerzhinskaya station
Dzerzhinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
D.
Traktorozavodskaya station
Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district of the city.
-
E.
Yelshanka station
Yelshanka station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
- 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: Kachinskaya station Triple: [Volgograd Metrotram, hasStation, Kachinskaya station]
Generated description
Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kachinskaya station Target entity description: Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
A.
Komsomolskaya station
Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
B.
Khimvolokno station
Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
C.
Dzerzhinskaya station
Dzerzhinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
-
D.
Traktorozavodskaya station
Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district of the city.
-
E.
Yelshanka station
Yelshanka station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
- 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb052e0a8819091bbc0da0e0a20fb |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6ae17a808190b5574ca6baafdb71 |
completed | March 9, 2026, 6:38 a.m. |
| NEDg | Description generation | batch_69ae6b73bb688190bcade17d991c4862 |
completed | March 9, 2026, 6:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae6be4431c81909c9b4ad82226215d |
completed | March 9, 2026, 6:42 a.m. |
Created at: March 4, 2026, 7:33 p.m.