Triple
T5254250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shin-Kobe Station |
E118659
|
entity |
| Predicate | distanceFromShinOsakaByShinkansen |
P61762
|
FINISHED |
| Object | approximately 28 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 28 km | Statement: [Shin-Kobe Station, distanceFromShinOsakaByShinkansen, approximately 28 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromShinOsakaByShinkansen Context triple: [Shin-Kobe Station, distanceFromShinOsakaByShinkansen, approximately 28 km]
-
A.
distanceFromOsaka
Indicates the measured distance between a given place or object and the city of Osaka.
-
B.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
-
C.
distanceFromKochi_km
Indicates the physical distance, measured in kilometers, between a given location and Kochi.
-
D.
distanceToSapporo
Indicates the measured or calculated distance between a given entity and the location of Sapporo.
-
E.
distanceToKyushu
Indicates the spatial distance between a given entity’s location and the region of Kyushu.
- 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7ba1cca88190bebd516851b9bf7f |
completed | March 20, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69bd77c30bac8190a883ca45da35d667 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd787975788190848ffbac87896efe |
completed | March 20, 2026, 4:40 p.m. |
Created at: March 20, 2026, 1:50 p.m.