Triple
T38460173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Trent Jones Jr. |
E912427
|
entity |
| Predicate | hasDesignedCoursesIn |
P201231
|
FINISHED |
| Object | North America |
—
|
NE NERFINISHED |
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: North America | Statement: [Robert Trent Jones Jr., hasDesignedCoursesIn, North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDesignedCoursesIn Context triple: [Robert Trent Jones Jr., hasDesignedCoursesIn, North America]
-
A.
taughtCourse
Indicates that an entity (typically an instructor) has taught a particular course.
-
B.
hasTaughtIn
Indicates that a person has taught or given instruction within a particular place, institution, or region.
-
C.
hasMultipleCourses
Indicates that an entity is associated with more than one course within the given context.
-
D.
hasTypicalCourse
Indicates that there is a characteristic or commonly observed progression, sequence, or development pattern associated with the subject.
-
E.
hasCourseThrough
Indicates that something (such as a path, route, or flow) passes through or traverses another entity or area.
- 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_69f76e861d8c81908559031dc66e3c15 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffdf47d9608190830ca23d9cef6409 |
completed | May 10, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69ffdf00e2b4819082dd5cb78f316baf |
completed | May 10, 2026, 1:27 a.m. |
| PDg | Predicate description generation | batch_69ffdf46e18c8190a5e4f4e5211cb087 |
completed | May 10, 2026, 1:28 a.m. |
Created at: May 3, 2026, 4:31 p.m.