Triple
T8094582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guiyang |
E188949
|
entity |
| Predicate | expresswayNetwork |
P3293
|
FINISHED |
| Object | connected to national expressways |
—
|
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: connected to national expressways | Statement: [Guiyang, expresswayNetwork, connected to national expressways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expresswayNetwork Context triple: [Guiyang, expresswayNetwork, connected to national expressways]
-
A.
motorwayServedBy
Indicates that a motorway is connected to or accessed by a particular service facility, route, or transport service.
-
B.
transportNetwork
Indicates a relationship where infrastructure or services enable the movement of people or goods between different locations.
-
C.
roadSystem
chosen
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
D.
numberOfRoadways
Indicates the count of distinct roadways associated with or present at a given entity or location.
-
E.
hasRoadNetworkType
Indicates the type or classification of road network associated with or present in an 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb429089cc81909e4625f9cc7e305f |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:30 p.m.