Triple
T35704578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balboa County Sheriff’s Department |
E1031682
|
entity |
| Predicate | hasSheriff |
P22466
|
FINISHED |
| Object | Keith Mars |
—
|
NE NERFINISHED |
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: Keith Mars | Statement: [Balboa County Sheriff’s Department, hasSheriff, Keith Mars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSheriff Context triple: [Balboa County Sheriff’s Department, hasSheriff, Keith Mars]
-
A.
hasCountySheriff
chosen
Indicates that a jurisdiction or area is served or overseen by a specific county sheriff.
-
B.
hasPoliceChief
Indicates that an entity has, is associated with, or is under the authority of a specific police chief.
-
C.
hasUnitedStatesMarshal
Indicates that an entity is associated with or served by a particular United States Marshal.
-
D.
hasPoliceDepartment
Indicates that an entity possesses, is served by, or is administratively associated with a police department.
-
E.
hasPolicePartner
Indicates that one entity has another entity as its partner in a police or law-enforcement context.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:05 p.m.