Triple
T14971684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mitakadai Station |
E373334
|
entity |
| Predicate | distanceFromShibuyaTerminus_km |
P116898
|
FINISHED |
| Object | 7.5 |
—
|
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: 7.5 | Statement: [Mitakadai Station, distanceFromShibuyaTerminus_km, 7.5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromShibuyaTerminus_km Context triple: [Mitakadai Station, distanceFromShibuyaTerminus_km, 7.5]
-
A.
distanceToShinjukuStation_km
Indicates the physical distance, measured in kilometers, between a given place and Shinjuku Station.
-
B.
distanceFromŌmiyaStation_km
Indicates the distance, measured in kilometers, between a given place and Ōmiya Station.
-
C.
distanceFromKyotoStation
Indicates the spatial distance between a given location and Kyoto Station.
-
D.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
E.
distanceFromNagasakiStation
Indicates the measured distance between a given place or object and Nagasaki 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e59a7c8190a1634a706ea68fda |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:50 a.m.