Triple
T31130752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longyang Road |
E793496
|
entity |
| Predicate | hasAssociatedMaglevStation |
P726
|
FINISHED |
| Object | Shanghai Maglev Longyang Road Station |
—
|
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: Shanghai Maglev Longyang Road Station | Statement: [Longyang Road, hasAssociatedMaglevStation, Shanghai Maglev Longyang Road Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedMaglevStation Context triple: [Longyang Road, hasAssociatedMaglevStation, Shanghai Maglev Longyang Road Station]
-
A.
hasHighSpeedRailStation
Indicates that a location is served by a high-speed rail station where high-speed trains regularly stop.
-
B.
hasMetroTerminus
Indicates that one location serves as the terminal (end) station of a metro line for another location.
-
C.
hasRailStation
chosen
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
hasMBTACommuterRailTerminus
Indicates that one entity serves as the endpoint or final stop of an MBTA Commuter Rail line for the other entity.
-
E.
hasLightRailStationPlanned
Indicates that a light rail station is planned or scheduled to be built at or associated with the 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
Created at: April 29, 2026, 9:05 p.m.