Triple
T14741330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Somerset v Stewart |
E346353
|
entity |
| Predicate | hasRemedySought |
P2242
|
FINISHED |
| Object | writ of habeas corpus |
—
|
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: writ of habeas corpus | Statement: [Somerset v Stewart, hasRemedySought, writ of habeas corpus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRemedySought Context triple: [Somerset v Stewart, hasRemedySought, writ of habeas corpus]
-
A.
remedySought
chosen
Indicates that a particular legal or corrective action is being requested as a solution or relief in response to a problem or dispute.
-
B.
hasRemedy
Indicates that one entity serves as a remedy, treatment, or corrective measure for a problem, condition, or undesirable state associated with another entity.
-
C.
hasReceivedTreatmentFor
Indicates that an entity has undergone or been given a treatment in relation to a specified condition, issue, or problem.
-
D.
hasTreatmentConsideration
Indicates that a particular factor, condition, or option should be taken into account when planning, selecting, or managing a treatment.
-
E.
usesTreatment
Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7345680819093e901233a064e48 |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.