Triple
T12459670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Memorial Tournament |
E297754
|
entity |
| Predicate | hasCourseRenovations |
P65316
|
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: [The Memorial Tournament, hasCourseRenovations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourseRenovations Context triple: [The Memorial Tournament, hasCourseRenovations, yes]
-
A.
courseRenovation
chosen
Indicates that a course is undergoing or has undergone changes or improvements to its structure, content, or delivery.
-
B.
hasRenovation
Indicates that an entity has undergone, is undergoing, or is associated with a renovation process or renovation event.
-
C.
hasMultipleCourses
Indicates that an entity is associated with more than one course within the given context.
-
D.
hasRebuiltCampus
Indicates that an entity has undertaken and completed the process of reconstructing or significantly renovating a campus.
-
E.
isAmongOldestCourses
Indicates that a course belongs to the subset of courses with the earliest or longest-standing origin within a given set or institution.
- F. None of above.
Provenance (3 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.