Triple
T25621260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Arbitration Act |
E642300
|
entity |
| Predicate | influencedAreaOfLaw |
P113669
|
FINISHED |
| Object | consumer arbitration |
—
|
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: consumer arbitration | Statement: [Federal Arbitration Act, influencedAreaOfLaw, consumer arbitration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedAreaOfLaw Context triple: [Federal Arbitration Act, influencedAreaOfLaw, consumer arbitration]
-
A.
notableAreaOfLaw
Indicates that a person or entity is particularly recognized or distinguished in a specific field or area of law.
-
B.
hasCommonLegalInfluence
Indicates that two or more entities are subject to, shaped by, or governed under the same legal authority, framework, or precedent.
-
C.
branchOfLaw
Indicates a relationship where one legal field or discipline is a subdivision or specialized area within a broader body of law.
-
D.
legalDoctrineInfluenced
Indicates that one legal doctrine has shaped, informed, or contributed to the development or interpretation of another legal doctrine.
-
E.
appliesToFieldOfLaw
chosen
Indicates that something is relevant or applicable to a particular field or branch of law.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 21, 2026, 5:05 p.m.