Triple
T20181680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenyang Metro |
E492741
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | Shenyang Metro Line 9 |
—
|
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: Shenyang Metro Line 9 | Statement: [Shenyang Metro, hasLine, Shenyang Metro Line 9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shenyang Metro Line 9 Context triple: [Shenyang Metro, hasLine, Shenyang Metro Line 9]
-
A.
Shenyang Metro
chosen
Shenyang Metro is the rapid transit system serving the city of Shenyang, China, providing urban rail transportation across multiple lines and key hubs.
-
B.
Dalian Metro
Dalian Metro is the rapid transit system serving the coastal city of Dalian in Liaoning Province, China, providing urban and suburban rail transportation.
-
C.
Harbin Metro
Harbin Metro is the rapid transit system serving the city of Harbin in northeastern China, providing urban rail transportation across the metropolitan area.
-
D.
Tianjin Metro Line 9
Tianjin Metro Line 9 is a rapid transit line in Tianjin, China, that connects the city center with eastern districts and key transport hubs.
-
E.
Changchun Rail Transit
Changchun Rail Transit is the urban rapid transit system serving Changchun, China, comprising multiple metro and light rail lines that connect key districts across the city.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668ef9370819091a8479f811002a9 |
completed | April 20, 2026, 5:57 p.m. |
Created at: April 11, 2026, 11:36 p.m.