Triple
T13140048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shijiazhuang Metro |
E312187
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 2
Line 2 is a rapid transit line of the Shijiazhuang Metro system in Shijiazhuang, Hebei, China.
|
E1024784
|
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 2 | Statement: [Shijiazhuang Metro, hasLine, Line 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 2 Context triple: [Shijiazhuang Metro, hasLine, Line 2]
-
A.
Line 2
Line 2 is one of the main lines of the Santiago Metro in Chile, running in a generally north–south direction and serving several central and densely populated areas of the city.
-
B.
Line 2
Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
-
C.
Line 2
Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
-
D.
Line 2
Line 2 is a major circular line of the Seoul Metropolitan Subway system, known for being one of the busiest and most important routes in the network.
-
E.
Line 2
Line 2 is a major rapid transit route of the STC Metro system, serving key districts along one of the network’s primary corridors.
- 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 2 Triple: [Shijiazhuang Metro, hasLine, Line 2]
Generated description
Line 2 is a rapid transit line of the Shijiazhuang Metro system in Shijiazhuang, Hebei, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 2 Target entity description: Line 2 is a rapid transit line of the Shijiazhuang Metro system in Shijiazhuang, Hebei, China.
-
A.
Line 2
Line 2 is a major east–west rapid transit route in the Shenzhen Metro system, connecting key commercial and residential districts across the city.
-
B.
Line 2
Line 2 is a major rapid transit route of the Guangzhou Metro system that runs through key urban districts and serves as one of the network’s primary north–south corridors.
-
C.
Line 2
Line 2 is a major rapid transit line of the Manila Light Rail Transit System in the Philippines, connecting several key cities across Metro Manila.
-
D.
Line 2
Line 2 is a major east–west rapid transit route of the Nanjing Metro system in Nanjing, China, connecting key urban districts and transportation hubs.
-
E.
Line 2
Line 2 is a major rapid transit line of the Chongqing Metro system in Chongqing, China, known for being one of the city's primary monorail corridors.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b84f1081908b9e2d54a64d4c2d |
completed | April 10, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eae2c3848190b062fa8da7dc8a92 |
completed | May 3, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69f6f01e9c488190ad52280903c074da |
completed | May 3, 2026, 6:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6f0e5f94c81908f4707913dc5dc92 |
completed | May 3, 2026, 6:53 a.m. |
Created at: April 9, 2026, 9:09 p.m.