Triple
T1768702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro |
E38822
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 14
Line 14 is a rapid transit line of the Shanghai Metro system that serves as one of the city's major east–west corridors.
|
E207164
|
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 14 | Statement: [Shanghai Metro, hasLine, Line 14]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 14 Context triple: [Shanghai Metro, hasLine, Line 14]
-
A.
Line 14
Line 14 is a major rapid transit line of the Beijing Subway system that serves multiple key residential and commercial districts across the city.
-
B.
Line 14
Line 14 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving suburban and outlying districts with high-speed, longer-distance urban rail service.
-
C.
Line 13
Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
-
D.
Line 13
Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
-
E.
Line 13
Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
- 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 14 Triple: [Shanghai Metro, hasLine, Line 14]
Generated description
Line 14 is a rapid transit line of the Shanghai Metro system that serves as one of the city's major east–west corridors.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 14 Target entity description: Line 14 is a rapid transit line of the Shanghai Metro system that serves as one of the city's major east–west corridors.
-
A.
Line 14
Line 14 is a major rapid transit line of the Beijing Subway system that serves multiple key residential and commercial districts across the city.
-
B.
Line 14
Line 14 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving suburban and outlying districts with high-speed, longer-distance urban rail service.
-
C.
Line 13
Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
-
D.
Line 13
Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
-
E.
Line 13
Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
- 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_69add1b679d88190b3c6e50c96f917e4 |
completed | March 8, 2026, 7:44 p.m. |
| NEDg | Description generation | batch_69add246f1a88190b3e14d1e45f5d433 |
completed | March 8, 2026, 7:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69add2afe284819083723ccaa2219222 |
completed | March 8, 2026, 7:49 p.m. |
Created at: March 4, 2026, 7:31 p.m.