Triple
T29573803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Denki University (near Kita-Senju) |
E753380
|
entity |
| Predicate | transportationModeAccess |
P147666
|
FINISHED |
| Object | railway |
—
|
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: railway | Statement: [Tokyo Denki University (near Kita-Senju), transportationModeAccess, railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportationModeAccess Context triple: [Tokyo Denki University (near Kita-Senju), transportationModeAccess, railway]
-
A.
transportModeAccess
Indicates that one entity has the ability or permission to use, reach, or be served by a particular mode of transportation.
-
B.
transportAccessType
chosen
Indicates the type or mode of transportation access available or used in a given context.
-
C.
hasTransitAccessTo
Indicates that one place or entity is reachable from another via public or shared transportation services.
-
D.
transportAccessFrom
Indicates that one location or entity has transportation access originating from another specified location or source.
-
E.
airportAccessMode
Indicates the typical mode or method of transportation used to access or reach an airport.
- 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_69f0ef7fcb4881908a933110adb9bda1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: April 28, 2026, 6 p.m.