Triple
T5092954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Labor Day Classic |
E114796
|
entity |
| Predicate | featuresInstitutionType |
P303
|
FINISHED |
| Object | historically black colleges and universities |
—
|
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: historically black colleges and universities | Statement: [Labor Day Classic, featuresInstitutionType, historically black colleges and universities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresInstitutionType Context triple: [Labor Day Classic, featuresInstitutionType, historically black colleges and universities]
-
A.
featuresInstitution
Indicates that one entity includes, presents, or highlights an institution as a notable component or participant.
-
B.
institutionalFeature
Indicates that something is a characteristic, structure, or property that defines or shapes an institution or institutional arrangement.
-
C.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
D.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
E.
universityCharacteristic
Indicates that a specified characteristic, quality, or attribute is associated with a particular university.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd754369708190bf4e171a904a19e1 |
completed | March 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69bd715c0a448190afc837c6c31dc6ab |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:40 p.m.