Triple
T33477520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacob Nighthorse |
E857365
|
entity |
| Predicate | hasLegalIssuesWith |
P4511
|
FINISHED |
| Object | Absaroka County Sheriff’s Department |
—
|
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: Absaroka County Sheriff’s Department | Statement: [Jacob Nighthorse, hasLegalIssuesWith, Absaroka County Sheriff’s Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalIssuesWith Context triple: [Jacob Nighthorse, hasLegalIssuesWith, Absaroka County Sheriff’s Department]
-
A.
hasLegalIssue
chosen
Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
-
B.
mainLegalIssue
Indicates the primary legal question or dispute that is central to a case or legal matter.
-
C.
hasOngoingLegalSignificance
Indicates that a legal matter, status, or decision continues to have current relevance, effect, or consequences under the law.
-
D.
hasLegalProceeding
Indicates that there is a formal legal action, case, or proceeding involving the related entities.
-
E.
hasLegalCharge
Indicates that one entity holds formal legal responsibility, authority, or custody over another entity or asset.
- 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 1, 2026, 1:38 a.m.