Triple
T2284795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takatsuki Station |
E51362
|
entity |
| Predicate | distanceFromKyotoStation |
P36170
|
FINISHED |
| Object | approximately 21 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 21 km | Statement: [Takatsuki Station, distanceFromKyotoStation, approximately 21 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKyotoStation Context triple: [Takatsuki Station, distanceFromKyotoStation, approximately 21 km]
-
A.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
B.
adjacentStationOnChuoLine
Indicates that two stations are directly next to each other as consecutive stops on the Chuo railway line.
-
C.
peakRouteMileage
Indicates the maximum total distance covered by a particular route over a specified period or under peak operating conditions.
-
D.
distanceFromTerminus
Indicates the measured distance of an entity from a defined endpoint or terminus along a route, path, or sequence.
-
E.
hasNearbyRailwayStation
Indicates that a railway station is located within a short or convenient distance from the referenced entity.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc245dd208190b13c5f5d05aa6990 |
completed | March 7, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69abbdbb9e4c819085fc588626ec7c09 |
completed | March 7, 2026, 5:55 a.m. |
| PDg | Predicate description generation | batch_69abbe1ecb7081909c2c66da08a48ab7 |
completed | March 7, 2026, 5:56 a.m. |
Created at: March 4, 2026, 7:48 p.m.