Triple
T11744921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John D. Hunter |
E279253
|
entity |
| Predicate | hasNotableStudentOrMentee |
P18487
|
FINISHED |
| Object | Matplotlib contributor community |
—
|
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: Matplotlib contributor community | Statement: [John D. Hunter, hasNotableStudentOrMentee, Matplotlib contributor community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableStudentOrMentee Context triple: [John D. Hunter, hasNotableStudentOrMentee, Matplotlib contributor community]
-
A.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
B.
notableStudentOrMentorRelationship
chosen
Indicates a notable educational or mentorship relationship between two individuals, where one has been a significant student or mentor of the other.
-
C.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
D.
hasNotableFacultyAlumnus
Indicates that an individual is a distinguished former student who is recognized as notable faculty at a given institution.
-
E.
hasNotableAlumniInstitution
Indicates that an institution is associated with one or more notable alumni who previously attended or graduated from it.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f2a38c8190a682d8dae1ab9415 |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a813cc48190a3dfdc60e8af80ae |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.