Triple
T16203816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michigan Appellate Reports |
E393268
|
entity |
| Predicate | typeOfLawMaterial |
P75075
|
FINISHED |
| Object | case law |
—
|
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: case law | Statement: [Michigan Appellate Reports, typeOfLawMaterial, case law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLawMaterial Context triple: [Michigan Appellate Reports, typeOfLawMaterial, case law]
-
A.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
B.
typeOfLawCollection
chosen
Indicates that a given collection is categorized as a specific type of law collection (e.g., by legal domain, jurisdiction, or purpose).
-
C.
legalMatters
Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
-
D.
typeOfLawReport
Indicates the specific category or classification of a law report (e.g., official, unofficial, regional, specialized) associated with a legal case or decision.
-
E.
subjectOfLaw
Indicates that a law, legal document, or legal provision is about, concerns, or applies to the referenced subject.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2270ca18c8190a259992aed4ec072 |
completed | April 17, 2026, 12:26 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.