Triple
T8659041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiamen–Shenzhen Railway |
E205499
|
entity |
| Predicate | railwayLineNumberOfTracks |
P17128
|
FINISHED |
| Object | double-track |
—
|
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: double-track | Statement: [Xiamen–Shenzhen Railway, railwayLineNumberOfTracks, double-track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayLineNumberOfTracks Context triple: [Xiamen–Shenzhen Railway, railwayLineNumberOfTracks, double-track]
-
A.
numberOfRailwayTracks
chosen
Indicates the quantity of railway tracks associated with or present at a given entity or location.
-
B.
numberOfRailLines
Indicates the total count of rail lines associated with or serving a given entity.
-
C.
railTracks
Indicates that one entity consists of, includes, or is associated with rail tracks used for guiding trains or rail vehicles.
-
D.
hasRailwayLineNumber
Indicates the specific identification number assigned to a railway line associated with an entity.
-
E.
railwayLineNumber
Indicates the identifying number assigned to a specific railway line within a rail network.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc486ece68819089c74bdf98b64490 |
completed | March 31, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:30 p.m.