Triple
T28163229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheryl Thomas |
E714949
|
entity |
| Predicate | isProfessorAt |
P132894
|
FINISHED |
| Object | University College London |
—
|
NE NERFINISHED |
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: University College London | Statement: [Cheryl Thomas, isProfessorAt, University College London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isProfessorAt Context triple: [Cheryl Thomas, isProfessorAt, University College London]
-
A.
isProfessorshipIn
Indicates that a professorship position is associated with or belongs to a specific academic field, department, or institution.
-
B.
isCoreFacultyOf
chosen
Indicates that a person holds a primary, central, and ongoing faculty appointment within a specific academic department, program, or institution.
-
C.
hasUniversityFaculty
Indicates that a university or academic institution employs or is associated with one or more faculty members.
-
D.
hasDoctoralDegreeFrom
Indicates that an individual holds a doctoral-level academic degree that was awarded by a specified institution.
-
E.
hasFacultyIn
Indicates that an institution or organization has faculty members associated with or working in a particular department, field, or academic unit.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f65876c52c8190bc889c7a67bd07f3 |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 10:07 p.m.