Triple
T25027151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Changsha Maglev Express |
E626740
|
entity |
| Predicate | adjacentTransportHub |
P99506
|
FINISHED |
| Object | Changsha Huanghua International Airport |
—
|
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: Changsha Huanghua International Airport | Statement: [Changsha Maglev Express, adjacentTransportHub, Changsha Huanghua International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentTransportHub Context triple: [Changsha Maglev Express, adjacentTransportHub, Changsha Huanghua International Airport]
-
A.
adjacentToStation
Indicates that one entity is located next to or immediately beside a station.
-
B.
hasAdjacentBusStation
Indicates that one location has a bus station situated directly next to or very near it.
-
C.
nearestMajorTransportHub
chosen
Indicates that one location is the closest significant transportation center (such as a major train station, airport, or bus terminal) to another location.
-
D.
nearbyTerminus
Indicates that one terminus (end point or final stop) is located close to another terminus in space.
-
E.
adjacentStationOnTransitway
Indicates that one station is directly next to another along the same transitway, with no other station in between.
- 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_69e2ff28ee3881909c626af002457a4a |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 18, 2026, 6:07 a.m.