Triple
T24798346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael DeLeon |
E620450
|
entity |
| Predicate | typeOfCaseInvolved |
P28693
|
FINISHED |
| Object | civil rights case |
—
|
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: civil rights case | Statement: [Michael DeLeon, typeOfCaseInvolved, civil rights case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCaseInvolved Context triple: [Michael DeLeon, typeOfCaseInvolved, civil rights case]
-
A.
litigationType
chosen
Indicates the specific category or nature of a legal dispute or court case associated with an entity or event.
-
B.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
C.
legalCase
Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
-
D.
legalCaseRelatedTo
Indicates that there is a relevant connection or association between a legal case and another entity, such as a person, organization, event, or legal matter.
-
E.
legalCaseAlongside
Indicates that two or more legal cases are proceeding in parallel or in coordination, such that they are related or handled together in some aspect of the legal process.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 18, 2026, 4:48 a.m.