Triple
T1303579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District Court of Maryland |
E27821
|
entity |
| Predicate | hasTypeOfProceeding |
P25382
|
FINISHED |
| Object | bench trials in many cases |
—
|
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: bench trials in many cases | Statement: [District Court of Maryland, hasTypeOfProceeding, bench trials in many cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfProceeding Context triple: [District Court of Maryland, hasTypeOfProceeding, bench trials in many cases]
-
A.
typeOfProceedings
chosen
Indicates the specific category or kind of legal or formal process under which an action or case is being conducted.
-
B.
hasLegalProceeding
Indicates that there is a formal legal action, case, or proceeding involving the related entities.
-
C.
hasTypeOfCourt
Indicates that an entity is associated with or classified by a specific type or category of court.
-
D.
legalProcedureUsed
Indicates that a particular legal procedure or process is applied or employed in relation to a case, action, or legal matter.
-
E.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c116d7d881908ee631258f80980e |
completed | March 1, 2026, 10:43 p.m. |
| PD | Predicate disambiguation | batch_69a4bee8544c8190874efd9bae9bccf9 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.