Triple
T15029432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanzhou railway station |
E378302
|
entity |
| Predicate | hasFreightFacilities |
P78734
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lanzhou railway station, hasFreightFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFreightFacilities Context triple: [Lanzhou railway station, hasFreightFacilities, yes]
-
A.
hasFreightFacility
chosen
Indicates that an entity is equipped with or connected to a facility used for handling, loading, unloading, or storing freight.
-
B.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
C.
hasRailFacility
Indicates that an entity possesses or is served by a rail-related facility, such as a railway station, terminal, or yard.
-
D.
hasGoodsFacilities
Indicates that a location or entity is equipped with facilities for handling, storing, or processing goods or cargo.
-
E.
hasCargoServices
Indicates that an entity provides or is equipped to handle cargo transportation or freight services for another entity or location.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e0e8c88190ac6f5786b4d4040f |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:59 a.m.