Triple
T20093697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chegongmiao station |
E496340
|
entity |
| Predicate | numberOfMetroLinesServed |
P18635
|
FINISHED |
| Object | 4 |
—
|
LITERAL FINISHED |
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: 4 | Statement: [Chegongmiao station, numberOfMetroLinesServed, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMetroLinesServed Context triple: [Chegongmiao station, numberOfMetroLinesServed, 4]
-
A.
isFirstMetroLineInCity
Indicates that a metro line is the earliest or original metro line established in a given city.
-
B.
monorailLines
Indicates that there is a monorail transit line or system associated with, serving, or present in the referenced entity.
-
C.
hasMetroLine
Indicates that a location or area is served by, or connected to, a specific metro (subway) line.
-
D.
subwayLine
Indicates that there is a subway line connection or service relationship between the referenced entities.
-
E.
numberOfRailLines
chosen
Indicates the total count of rail lines associated with or serving a given entity.
- F. None of above.
Provenance (3 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666a7a94819080ebabfba9762f97 |
completed | April 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:23 p.m.