Triple
T1201530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ED |
E25791
|
entity |
| Predicate | typeOfDepartment |
P658
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [ED, typeOfDepartment, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfDepartment Context triple: [ED, typeOfDepartment, education]
-
A.
departmentType
chosen
Indicates the classification or category of a department, specifying what kind of department it is.
-
B.
department
Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
-
C.
departmentNumber
Indicates the specific numeric code assigned to identify a particular department within an organization or system.
-
D.
typeOfMinistry
Indicates the specific category or kind of ministry that an entity belongs to or represents.
-
E.
typeOfRole
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9fece4819089a6a2d61e61fa2e |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.