Triple
T1768707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro |
E38822
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 19
Line 19 is a planned rapid transit line of the Shanghai Metro network intended to serve additional urban and suburban areas of the city.
|
E221623
|
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 19 | Statement: [Shanghai Metro, hasLine, Line 19]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 19 Context triple: [Shanghai Metro, hasLine, Line 19]
-
A.
Line 19
Line 19 is a north–south rapid transit line of the Beijing Subway designed to improve connectivity between the city's central districts and its outer areas.
-
B.
Line 18
Line 18 is a rapid transit line of the Shanghai Metro system serving various districts in Shanghai, China.
-
C.
Line 18
Line 18 is a high-speed rapid transit line of the Guangzhou Metro system in Guangzhou, China.
-
D.
Line 17
Line 17 is a rapid transit line of the Beijing Subway system designed to improve north–south connectivity across the city.
-
E.
Line 17
Line 17 is a suburban rapid transit line of the Shanghai Metro that primarily serves the western districts of the city, connecting urban Shanghai with outlying residential and developing 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 19 Triple: [Shanghai Metro, hasLine, Line 19]
Generated description
Line 19 is a planned rapid transit line of the Shanghai Metro network intended to serve additional urban and suburban areas of the city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 19 Target entity description: Line 19 is a planned rapid transit line of the Shanghai Metro network intended to serve additional urban and suburban areas of the city.
-
A.
Line 19
Line 19 is a north–south rapid transit line of the Beijing Subway designed to improve connectivity between the city's central districts and its outer areas.
-
B.
Line 18
Line 18 is a rapid transit line of the Shanghai Metro system serving various districts in Shanghai, China.
-
C.
Line 18
Line 18 is a high-speed rapid transit line of the Guangzhou Metro system in Guangzhou, China.
-
D.
Line 17
Line 17 is a rapid transit line of the Beijing Subway system designed to improve north–south connectivity across the city.
-
E.
Line 17
Line 17 is a suburban rapid transit line of the Shanghai Metro that primarily serves the western districts of the city, connecting urban Shanghai with outlying residential and developing 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648d9f2c8190aca4884648a69eb0 |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae030371e88190982c822a460d3e47 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae039a7c948190b8b4b4c2045007d3 |
completed | March 8, 2026, 11:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae04253a80819092c112faddec1de1 |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:31 p.m.