Triple
T10011922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadovaya metro station |
E199393
|
entity |
| Predicate | line |
P1293
|
FINISHED |
| Object |
Line 5
Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
|
E834773
|
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: Line 5 | Statement: [Sadovaya metro station, line, Line 5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 5 Context triple: [Sadovaya metro station, line, Line 5]
-
A.
Line 5
Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
-
B.
Line 5
Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
-
C.
Line 5
Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
-
D.
Line 5
Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
-
E.
Line 5
Line 5 is a major east–west rapid transit line of the Seoul Metropolitan Subway system in South Korea, serving key districts across the city and extending into surrounding areas.
- 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: Line 5 Triple: [Sadovaya metro station, line, Line 5]
Generated description
Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 5 Target entity description: Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
-
A.
Line 5
Line 5 is a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs across the city.
-
B.
Line 5
Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
-
C.
Line 5
Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
-
D.
Line 5
Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
-
E.
Line 5
Line 5 is a major east–west rapid transit line of the Seoul Metropolitan Subway system in South Korea, serving key districts across the city and extending into surrounding areas.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd3cf5b881908f5318e55bdd22b6 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26a7b0ce08190b6109ddbc0b05362 |
completed | April 5, 2026, 1:58 p.m. |
| NEDg | Description generation | batch_69d26b6d52e8819082fed0bfdaf48e4c |
completed | April 5, 2026, 2:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d26c47d25081908818f18f6b0881b2 |
completed | April 5, 2026, 2:06 p.m. |
Created at: March 30, 2026, 8:52 p.m.