Triple
T19976799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broderick Fobbs |
E493712
|
entity |
| Predicate | coachedInstitutionType |
P74507
|
FINISHED |
| Object | historically black college or university |
—
|
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 college or university | Statement: [Broderick Fobbs, coachedInstitutionType, historically black college or university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachedInstitutionType Context triple: [Broderick Fobbs, coachedInstitutionType, historically black college or university]
-
A.
trainingInstitution
Indicates that one entity serves as the institution or organization where another entity receives training or education.
-
B.
typeOfInstitution
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
C.
coachSchool
chosen
Indicates that a person serves as a coach for a particular school or educational institution.
-
D.
governsInstitutionType
Indicates that an entity has authoritative control or regulatory oversight over a particular type or category of institution.
-
E.
associatedInstitutionType
Indicates the type or category of institution with which an entity is associated.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d1054e08190993b92b86ec5bbc8 |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:27 p.m.