Triple
T1874274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Mullins |
E39103
|
entity |
| Predicate | caseTypeInvolved |
P29037
|
FINISHED |
| Object | public accommodations discrimination |
—
|
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: public accommodations discrimination | Statement: [David Mullins, caseTypeInvolved, public accommodations discrimination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseTypeInvolved Context triple: [David Mullins, caseTypeInvolved, public accommodations discrimination]
-
A.
legalCase
Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
-
B.
statuteInvolved
Indicates that a particular statute or legal provision is implicated, referenced, or applied in relation to a given case, event, or legal matter.
-
C.
involvesIssue
chosen
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
-
D.
disputeInvolves
Indicates that a particular dispute includes or concerns the specified entities as participants or parties to the conflict.
-
E.
associatedCourtCase
Indicates a relationship where one entity is linked to, or involved in, a particular court 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0f79fbc819085c54f3189a552d9 |
completed | March 7, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69abafe2b56c81909e13d543982e6e13 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.