Triple
T8303429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Park Pitch and Putt |
E194400
|
entity |
| Predicate | hasCourseLength |
P82629
|
FINISHED |
| Object | short-hole layout |
—
|
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: short-hole layout | Statement: [Central Park Pitch and Putt, hasCourseLength, short-hole layout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourseLength Context triple: [Central Park Pitch and Putt, hasCourseLength, short-hole layout]
-
A.
courseLength
Indicates the duration or total length of a course, typically measured in units such as hours, weeks, or credits.
-
B.
approximateCourseLength
Indicates an estimated or rough value for the length or duration of a course rather than an exact measurement.
-
C.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
D.
numberOfCourses
Indicates the quantity of courses associated with a given entity.
-
E.
hasStructureOnCourse
Indicates that a physical structure is located on, along, or directly associated with a specific course or route.
- 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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7e8b9f6081909100d1da8a078616 |
completed | March 31, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69cb70bb3a708190bc705222092da614 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:53 p.m.