Triple
T6001111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wagon Wheel rivalry |
E133596
|
entity |
| Predicate | hasStudentSectionTraditions |
P67940
|
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: [Wagon Wheel rivalry, hasStudentSectionTraditions, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudentSectionTraditions Context triple: [Wagon Wheel rivalry, hasStudentSectionTraditions, yes]
-
A.
hasStudentTraditions
Indicates that an institution or group maintains specific customs, rituals, or practices that are regularly carried out by its students.
-
B.
hasStudentSection
Indicates that an entity (such as a course or class) is associated with a specific student section or subgroup of enrolled students.
-
C.
featuresStudentSections
Indicates that something includes or provides specific sections or groupings designated for students.
-
D.
studentSection
Indicates a relationship where a student is enrolled in or associated with a particular course section.
-
E.
hasStudentOrganization
Indicates that an entity (such as an institution or department) is associated with or hosts a particular student organization.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04ee7c0e08190a6e78969448b070a |
completed | March 22, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c049e152e88190979ab80cb9b50321 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:05 p.m.