Triple
T27548924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colin Michael Foale |
E695437
|
entity |
| Predicate | hasDoctoralDegree |
P167323
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Colin Michael Foale, hasDoctoralDegree, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDoctoralDegree Context triple: [Colin Michael Foale, hasDoctoralDegree, yes]
-
A.
hasDoctoralTraining
Indicates that one entity has received doctoral-level academic or professional training, typically under the supervision or within the program of another entity.
-
B.
hasDoctoralSchool
Indicates that an individual or academic entity is affiliated with or obtained their doctoral education from a specific doctoral school or graduate institution.
-
C.
hasDoctoralProgram
Indicates that an institution or academic unit offers and administers a doctoral-level degree program.
-
D.
hasDoctoralDegreeFrom
Indicates that an individual holds a doctoral-level academic degree that was awarded by a specified institution.
-
E.
isDoctorOf
Indicates that one entity serves as the medical doctor responsible for the care or treatment of another entity.
- F. None of above. chosen
Provenance (4 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_69ef5386c3e08190bfe33aa326e1f72b |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f66a6468ec8190a43ed6cd8c797f42 |
completed | May 2, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 27, 2026, 1:34 p.m.