Triple
T20260605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sendai Station |
E498821
|
entity |
| Predicate | distanceFromTokyoByRail_km |
P25290
|
FINISHED |
| Object | approximately 350 |
—
|
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 350 | Statement: [Sendai Station, distanceFromTokyoByRail_km, approximately 350]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTokyoByRail_km Context triple: [Sendai Station, distanceFromTokyoByRail_km, approximately 350]
-
A.
distanceFromTokyo
chosen
Indicates the physical distance between a given location and Tokyo.
-
B.
distanceToShinjukuStation_km
Indicates the physical distance, measured in kilometers, between a given place and Shinjuku Station.
-
C.
distanceFromShibuyaTerminus_km
Indicates the distance, measured in kilometers, from the Shibuya terminus to the referenced location or entity.
-
D.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
E.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674ca77c081909cd2f44ccfe3662d |
completed | April 20, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69e55b1b23f88190bdcbe2f81dd226dd |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:41 p.m.