Triple
T27408393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mishima Station |
E692072
|
entity |
| Predicate | distanceFromTokyoStationOnTokaidoShinkansen_km |
P199853
|
FINISHED |
| Object | 120.7 |
—
|
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: 120.7 | Statement: [Mishima Station, distanceFromTokyoStationOnTokaidoShinkansen_km, 120.7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTokyoStationOnTokaidoShinkansen_km Context triple: [Mishima Station, distanceFromTokyoStationOnTokaidoShinkansen_km, 120.7]
-
A.
distanceFromTokyoStationOnTokaidoMainLine_km
Indicates the distance in kilometers of a location measured along the Tokaido Main Line from Tokyo Station.
-
B.
distanceFromShinOsakaByShinkansen
Indicates the travel distance between a given location and Shin-Osaka Station when using the Shinkansen (bullet train).
-
C.
distanceFromShibuyaTerminus_km
Indicates the distance, measured in kilometers, from the Shibuya terminus to the referenced location or entity.
-
D.
distanceToShinjukuStation_km
Indicates the physical distance, measured in kilometers, between a given place and Shinjuku Station.
-
E.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
- 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_69ef5205fc808190ad3efc5525b8e6d6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69ff5f5ecc808190b2df364da108ff4c |
completed | May 9, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69ff5b84131c8190bf81d7fb53e934bc |
completed | May 9, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69ff5f5ddfcc819092563419f9e82d60 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 27, 2026, 12:31 p.m.