Triple
T18932415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liuliqiao station |
E463146
|
entity |
| Predicate | servesLine |
P839
|
FINISHED |
| Object | Line 10 |
—
|
NE NERFINISHED |
How this triple was built (2 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 10 | Statement: [Liuliqiao station, servesLine, Line 10]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 10 Context triple: [Liuliqiao station, servesLine, Line 10]
-
A.
Line 10
Line 10 is a rapid transit line of the Chongqing Metro system in Chongqing, China, providing urban rail service across parts of the municipality.
-
B.
Line 10
chosen
Line 10 is a major loop line of the Beijing Subway that encircles central urban districts and serves as a key transfer route in the network.
-
C.
Line 10
Line 10 is a major Shanghai Metro route known for serving central districts and key hubs such as Hongqiao Transportation Hub and the city’s historic and commercial areas.
-
D.
Line 10
Line 10 is a trolleybus route within Geneva’s public transport system that connects key districts and suburbs of the city.
-
E.
Line 10
Line 10 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key residential and commercial districts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3e498308190bd1594cca841199c |
completed | April 20, 2026, 7:21 a.m. |
Created at: April 10, 2026, 11:59 a.m.