Triple
T18146563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Station to Station |
E434405
|
entity |
| Predicate | containsNumberOfTracks |
P1707
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Station to Station, containsNumberOfTracks, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsNumberOfTracks Context triple: [Station to Station, containsNumberOfTracks, 6]
-
A.
numberOfTracks
chosen
Indicates the quantity of tracks associated with a given entity.
-
B.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
-
C.
hasTwoTracks
Indicates that the subject possesses or is associated with exactly two distinct tracks or pathways.
-
D.
containsHiddenTrack
Indicates that one media item includes another track that is not immediately apparent or listed, such as a hidden or uncredited track on an album.
-
E.
hasSingleTrackSections
Indicates that a route or railway line includes sections where only a single track is available for traffic.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de34bb608190a4842e86f2912dec |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.