Triple
T4408870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Secretary of State |
E94800
|
entity |
| Predicate | hasNoFixedDepartment |
P4926
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [First Secretary of State, hasNoFixedDepartment, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoFixedDepartment Context triple: [First Secretary of State, hasNoFixedDepartment, true]
-
A.
notTiedToSingleDepartment
chosen
Indicates that the entity is not exclusively associated with or restricted to a single department.
-
B.
canHoldAppointmentsInMultipleDepartments
Indicates that an entity is allowed to have appointments or roles in more than one department at the same time.
-
C.
offeredByDepartment
Indicates that something, such as a course or program, is provided or made available by a specific department.
-
D.
hasDepartmentSeatRole
Indicates that an entity holds a specific role or position associated with a seat in a particular department.
-
E.
department
Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
- 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3548cb92881908a3f98466da8e0a2 |
completed | March 13, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69b34f5b36a881909bf2e970aa523390 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:28 p.m.