Triple
T35318889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chūō Shinkansen |
E1019981
|
entity |
| Predicate | plannedLineLengthTokyoOsaka |
P192522
|
FINISHED |
| Object | over 400 km |
—
|
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: over 400 km | Statement: [Chūō Shinkansen, plannedLineLengthTokyoOsaka, over 400 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedLineLengthTokyoOsaka Context triple: [Chūō Shinkansen, plannedLineLengthTokyoOsaka, over 400 km]
-
A.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
B.
distanceFromOsaka
Indicates the measured distance between a given place or object and the city of Osaka.
-
C.
travelTimeFromTokyoByShinkansen
Indicates the amount of time required to travel from Tokyo to another location using the Shinkansen (bullet train).
-
D.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
E.
distanceFromNagoyaCityCenterKilometers
Indicates the distance, measured in kilometers, between an entity and the center of Nagoya City.
- 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_69f76de9d45c81908a2ed0956b448b65 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69fd0d0aebac8190868a7714ddb4f1fd |
completed | May 7, 2026, 10:07 p.m. |
Created at: May 3, 2026, 4:03 p.m.