Triple
T34300213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morioka Station |
E880148
|
entity |
| Predicate | distanceFromTokyoOnTōhokuShinkansen |
P205391
|
FINISHED |
| Object | approximately 535 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: approximately 535 km | Statement: [Morioka Station, distanceFromTokyoOnTōhokuShinkansen, approximately 535 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTokyoOnTōhokuShinkansen Context triple: [Morioka Station, distanceFromTokyoOnTōhokuShinkansen, approximately 535 km]
-
A.
distanceFromTokyoStationOnTokaidoShinkansen_km
Indicates the distance in kilometers from Tokyo Station to a given location along the Tokaido Shinkansen line.
-
B.
distanceFromTokyoStationOnTokaidoMainLine_km
Indicates the distance in kilometers of a location measured along the Tokaido Main Line from Tokyo Station.
-
C.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
D.
travelTimeFromTokyoByShinkansen
Indicates the amount of time required to travel from Tokyo to another location using the Shinkansen (bullet train).
-
E.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
- 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_69f349b79f6c81909cb468c92c39c74d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:57 a.m.