Triple
T1910707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Hongqiao Railway Station |
E38102
|
entity |
| Predicate | transportModeIntegration |
P33879
|
FINISHED |
| Object | high-speed rail |
—
|
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: high-speed rail | Statement: [Shanghai Hongqiao Railway Station, transportModeIntegration, high-speed rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportModeIntegration Context triple: [Shanghai Hongqiao Railway Station, transportModeIntegration, high-speed rail]
-
A.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
B.
transportHubType
Indicates the specific category or kind of transport hub associated with an entity (e.g., airport, train station, bus terminal).
-
C.
transportationFunction
Indicates that one entity serves to move or carry another entity from one place to another.
-
D.
publicTransitMode
Indicates the type of public transportation (e.g., bus, train, subway) used or associated with a given trip or segment.
-
E.
transports
Indicates that one entity carries or conveys another entity from one place to another.
- F. None of above. chosen
Provenance (4 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafeba3d88190afcce67483d8625b |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb34c4a64819096e12b152b84c334 |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:35 p.m.