Triple
T35318881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chūō Shinkansen |
E1019981
|
entity |
| Predicate | plannedTravelTimeTokyoOsaka |
P110673
|
FINISHED |
| Object | about 67 minutes |
—
|
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: about 67 minutes | Statement: [Chūō Shinkansen, plannedTravelTimeTokyoOsaka, about 67 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plannedTravelTimeTokyoOsaka Context triple: [Chūō Shinkansen, plannedTravelTimeTokyoOsaka, about 67 minutes]
-
A.
travelTimeFromTokyoByShinkansen
chosen
Indicates the amount of time required to travel from Tokyo to another location using the Shinkansen (bullet train).
-
B.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
C.
bestTravelTime
Indicates the most optimal duration or period required to travel between specified locations under given conditions.
-
D.
travelTimeOnShanghaiRoute
Indicates the duration required to travel along a specified route in Shanghai.
-
E.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
- 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_69f76de9d45c81908a2ed0956b448b65 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
Created at: May 3, 2026, 4:03 p.m.