Triple
T15466296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crossing Cup |
E372037
|
entity |
| Predicate | hasRetroCourses |
P118346
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Crossing Cup, hasRetroCourses, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetroCourses Context triple: [Crossing Cup, hasRetroCourses, yes]
-
A.
hasTypicalCourse
Indicates that there is a characteristic or commonly observed progression, sequence, or development pattern associated with the subject.
-
B.
hasMultipleCourses
Indicates that an entity is associated with more than one course within the given context.
-
C.
isAmongOldestCourses
Indicates that a course belongs to the subset of courses with the earliest or longest-standing origin within a given set or institution.
-
D.
isHistoricCourse
Indicates that a course has historical significance, typically due to its age, legacy, or notable past events associated with it.
-
E.
hasPar3Course
Indicates that an entity (such as a golf facility or location) includes or is associated with a par-3 golf course.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f680cec8190836a5ec841dee224 |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded284bd008190b31c53b4f1cebadd |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded5deee00819099fa3e43313312e1 |
completed | April 15, 2026, 12:03 a.m. |
Created at: April 10, 2026, 3:33 a.m.