Triple
T1632692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Oregon in Multnomah County criminal cases |
E35290
|
entity |
| Predicate | seeksRemedyType |
P13744
|
FINISHED |
| Object | criminal conviction |
—
|
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: criminal conviction | Statement: [State of Oregon in Multnomah County criminal cases, seeksRemedyType, criminal conviction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seeksRemedyType Context triple: [State of Oregon in Multnomah County criminal cases, seeksRemedyType, criminal conviction]
-
A.
remedySought
Indicates that a particular legal or corrective action is being requested as a solution or relief in response to a problem or dispute.
-
B.
typeOfRemedy
chosen
Indicates that one entity is a specific kind or category of remedy in relation to another entity.
-
C.
remedy
Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting another entity.
-
D.
typeOfClaim
Indicates the specific category or nature of a claim being made in relation to an entity or statement.
-
E.
litigationType
Indicates the specific category or nature of a legal dispute or court case associated with an entity or event.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907cac610819083cafd4396b6d66c |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.