Triple
T8165113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | County Manager of Arlington County |
E190671
|
entity |
| Predicate | appointerType |
P81048
|
FINISHED |
| Object | elected county board |
—
|
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: elected county board | Statement: [County Manager of Arlington County, appointerType, elected county board]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appointerType Context triple: [County Manager of Arlington County, appointerType, elected county board]
-
A.
appointmentType
Indicates the specific category or nature of an appointment associated with an entity or event.
-
B.
appointmentBy
Indicates that one entity is appointed or designated to a role, position, or task by another entity.
-
C.
appointmentTerm
Indicates the duration or specific period for which an appointment, position, or role is held.
-
D.
appointmentBody
Indicates that one entity serves as the main content or body text associated with a particular appointment.
-
E.
appointedFor
Indicates that an entity has been officially assigned or designated to perform a specific role, task, or function for another entity or purpose.
- 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_69ca82c0ef14819083713f4473dd847c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb466698108190ba6aa625e9182b2a |
completed | March 31, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb40a017608190b6b48cf60335fa8d |
completed | March 31, 2026, 3:33 a.m. |
Created at: March 30, 2026, 5:38 p.m.