Triple
T6314023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utsunomiya Station |
E141570
|
entity |
| Predicate | distanceFromTokyoStation |
P25290
|
FINISHED |
| Object | 98.6 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: 98.6 km | Statement: [Utsunomiya Station, distanceFromTokyoStation, 98.6 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTokyoStation Context triple: [Utsunomiya Station, distanceFromTokyoStation, 98.6 km]
-
A.
distanceFromTokyo
chosen
Indicates the physical distance between a given location and Tokyo.
-
B.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
-
C.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
D.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
E.
distanceFromKyoto
Indicates the measured spatial distance between a given entity’s location and the city of Kyoto.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064a075dc8190acf7ec010cb4b00c |
completed | March 22, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.