Triple
T34462562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Columbia v. John R. Thompson Co. |
E884683
|
entity |
| Predicate | typeOfLawInvolved |
P6527
|
FINISHED |
| Object | civil rights 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: civil rights law | Statement: [District of Columbia v. John R. Thompson Co., typeOfLawInvolved, civil rights law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLawInvolved Context triple: [District of Columbia v. John R. Thompson Co., typeOfLawInvolved, civil rights law]
-
A.
typeOfLaw
chosen
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
B.
litigationType
Indicates the specific category or nature of a legal dispute or court case associated with an entity or event.
-
C.
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.
-
D.
branchOfLaw
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
-
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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a013b78bde881909a082beced4e0157 |
completed | May 11, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_6a013acf45508190a999b208066072bd |
completed | May 11, 2026, 2:11 a.m. |
Created at: May 1, 2026, 2 a.m.