Triple
T13903340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hangzhou Metro |
E334282
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 6
Line 6 is a rapid transit line of the Hangzhou Metro system in Hangzhou, China, serving as part of the city's expanding urban rail network.
|
E1068772
|
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 6 | Statement: [Hangzhou Metro, hasLine, Line 6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 6 Context triple: [Hangzhou Metro, hasLine, Line 6]
-
A.
Line 6
Line 6 is a route of Mexico City’s Metrobús bus rapid transit system that serves as one of the network’s main corridors.
-
B.
Line 6
Line 6 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving multiple urban districts with frequent subway service.
-
C.
Line 6
Line 6 is a Culver CityBus route in the Los Angeles area that provides local and regional public transit service connecting key neighborhoods and transit hubs.
-
D.
Line 6
Line 6 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving multiple districts across the city.
-
E.
Line 6
Line 6 is one of the lines of the Paris Métro, known for its largely elevated route offering views of the city, including the Eiffel Tower.
- 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 6 Triple: [Hangzhou Metro, hasLine, Line 6]
Generated description
Line 6 is a rapid transit line of the Hangzhou Metro system in Hangzhou, China, serving as part of the city's expanding urban rail network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 6 Target entity description: Line 6 is a rapid transit line of the Hangzhou Metro system in Hangzhou, China, serving as part of the city's expanding urban rail network.
-
A.
Line 6
Line 6 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving multiple urban districts with frequent subway service.
-
B.
Line 6
Line 6 is a rapid transit line of the Shanghai Metro system serving several districts along the city’s eastern side.
-
C.
Line 6
Line 6 is a rapid transit line of the Chongqing Rail Transit system in Chongqing, China, serving key urban districts with high-capacity metro service.
-
D.
Line 6
Line 6 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving multiple districts across the city.
-
E.
Line 6
Line 6 is a planned rapid transit route within the future Ho Chi Minh City Metro system in Vietnam.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25db1e308190aaed6a21e443cc44 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c722e72081909090b2d64000ebd9 |
completed | May 3, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69f7c83a3e04819097b6e0b5a3161b9a |
completed | May 3, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c9732d188190a8a7151d21e0a310 |
completed | May 3, 2026, 10:17 p.m. |
Created at: April 9, 2026, 10:16 p.m.