Triple
T17916585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhuxinzhuang station |
E447941
|
entity |
| Predicate | servesLine |
P839
|
FINISHED |
| Object | Line 19 |
—
|
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 19 | Statement: [Zhuxinzhuang station, servesLine, Line 19]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 19 Context triple: [Zhuxinzhuang station, servesLine, Line 19]
-
A.
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.
-
B.
Line 19
chosen
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.
-
C.
Line 18
Line 18 is a planned rapid transit line of the Chongqing Metro system in Chongqing, China.
-
D.
Line 18
Line 18 is a rapid transit line of the Shanghai Metro system serving various districts in Shanghai, China.
-
E.
Line 18
Line 18 is a high-speed rapid transit line of the Guangzhou Metro system in Guangzhou, China.
- 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a3062bfc819083f7c0521bad4db8 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 10:20 a.m.