Triple
T34061974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomasina Coverly |
E873514
|
entity |
| Predicate | hasTutor |
P52943
|
FINISHED |
| Object | Septimus Hodge |
—
|
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: Septimus Hodge | Statement: [Thomasina Coverly, hasTutor, Septimus Hodge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTutor Context triple: [Thomasina Coverly, hasTutor, Septimus Hodge]
-
A.
hasTeacher
chosen
Indicates that one entity serves as an instructor or educator for another entity.
-
B.
hasTutorialIn
Indicates that one entity provides or includes a tutorial within the context or medium of another entity.
-
C.
hasLecturer
Indicates that an educational course, class, or module is taught or overseen by a specific lecturer.
-
D.
hasTeaching
Indicates that one entity provides instruction or educational guidance to another entity.
-
E.
hasTeacherType
Indicates that an entity is associated with a teacher characterized by a specific type or category (e.g., role, specialization, or employment status).
- 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_69f349a4af208190afa14888f9c9fb9d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70b9d235881908d6f8c60dfc73fc1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:52 a.m.