Triple
T22780326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpensia Cross-Country Centre |
E563818
|
entity |
| Predicate | hasMinimumCourseLength |
P149699
|
FINISHED |
| Object | 1.5 kilometres |
—
|
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: 1.5 kilometres | Statement: [Alpensia Cross-Country Centre, hasMinimumCourseLength, 1.5 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinimumCourseLength Context triple: [Alpensia Cross-Country Centre, hasMinimumCourseLength, 1.5 kilometres]
-
A.
hasCourseLength
Indicates that an entity (such as a course) is associated with a specific duration or length.
-
B.
hasCourseLengthUnit
Indicates the unit of measurement used to express the length or duration of a course.
-
C.
requiresMinimumTeachingHours
Indicates that one entity must provide at least a specified number of teaching hours to satisfy a requirement or condition for another entity or context.
-
D.
courseLength
Indicates the duration or total length of a course, typically measured in units such as hours, weeks, or credits.
-
E.
hasMinimum
Indicates that an entity possesses at least a specified lower bound or smallest allowable value, quantity, or level in relation to another entity or constraint.
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c2cab0881908df1d0629b43d350 |
completed | April 29, 2026, 3:34 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:28 p.m.