Triple
T6197261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zushi Station |
E138539
|
entity |
| Predicate | distanceFromTokyoStationOnYokosukaLine |
P69606
|
FINISHED |
| Object | about 56.8 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: about 56.8 km | Statement: [Zushi Station, distanceFromTokyoStationOnYokosukaLine, about 56.8 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTokyoStationOnYokosukaLine Context triple: [Zushi Station, distanceFromTokyoStationOnYokosukaLine, about 56.8 km]
-
A.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
-
B.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
C.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
D.
distanceToKyushu
Indicates the spatial distance between a given entity’s location and the region of Kyushu.
-
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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062508f5c8190a00291708a9a7de9 |
completed | March 22, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c055fbce1081908805fd12e242ab96 |
completed | March 22, 2026, 8:50 p.m. |
| PDg | Predicate description generation | batch_69c056c87340819088003f427706ebf8 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:20 p.m.