Triple
T10343434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angela Alioto |
E243681
|
entity |
| Predicate | genreOfLegalWork |
P73686
|
FINISHED |
| Object | civil rights 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: civil rights cases | Statement: [Angela Alioto, genreOfLegalWork, civil rights cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfLegalWork Context triple: [Angela Alioto, genreOfLegalWork, civil rights cases]
-
A.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
B.
juridicalCategory
Indicates the legal classification or status under which an entity or relationship is formally recognized in a juridical system.
-
C.
legalTextTypeWorkedOn
Indicates that an entity has worked on or handled a specific type or category of legal text.
-
D.
branchOfLaw
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
-
E.
legalGenre
chosen
Indicates that one entity is classified as a legal genre or category of law-related content for the other 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e92105888190a08104deb9d0cf1c |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4df9dc3208190bf1bd106f44f6202 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:55 a.m.