Triple
T1335423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William H. Foege |
E28736
|
entity |
| Predicate | hasAcademicBackgroundIn |
P27881
|
FINISHED |
| Object | medicine |
—
|
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: medicine | Statement: [William H. Foege, hasAcademicBackgroundIn, medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcademicBackgroundIn Context triple: [William H. Foege, hasAcademicBackgroundIn, medicine]
-
A.
hasAcademicFunction
Indicates that an entity serves a specific academic role, duty, or function within an educational or scholarly context.
-
B.
hasAcademicAffiliation
Indicates that an entity is formally associated with an academic institution, such as through employment, enrollment, or official collaboration.
-
C.
hasAcademicRank
Indicates that an entity holds a specific academic rank or title within an educational or research institution.
-
D.
hasDoctoralSchool
Indicates that an individual or academic entity is affiliated with or obtained their doctoral education from a specific doctoral school or graduate institution.
-
E.
hasAcademicOffice
Indicates that an entity maintains or occupies an official academic office or workspace associated with an educational or research institution.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1eb119881909dd5fbf728d9e8ba |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c1bf31988190a659f48fe018f4bc |
completed | March 1, 2026, 10:46 p.m. |
Created at: March 1, 2026, 7:55 p.m.