Triple
T28645170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephanie Edwards |
E725031
|
entity |
| Predicate | worksDepartment |
P81960
|
FINISHED |
| Object | general surgery |
—
|
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: general surgery | Statement: [Stephanie Edwards, worksDepartment, general surgery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksDepartment Context triple: [Stephanie Edwards, worksDepartment, general surgery]
-
A.
worksInDepartment
chosen
Indicates that an entity is employed in and performs their job duties within a particular department.
-
B.
workDivision
Indicates how a task, responsibility, or set of activities is split and allocated among multiple entities.
-
C.
department
Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
-
D.
propDepartment
Indicates that one entity functions as a department or organizational subdivision associated with another entity.
-
E.
motherDepartment
Indicates that one department is the parent or higher-level organizational unit of another department.
- 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_69f01d8423888190bd2f4e52605bf261 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 28, 2026, 4:47 a.m.