Triple
T1440494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Price Waterhouse v. Hopkins |
E31057
|
entity |
| Predicate | employerBurdenStandard |
P29341
|
FINISHED |
| Object | preponderance of the evidence |
—
|
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: preponderance of the evidence | Statement: [Price Waterhouse v. Hopkins, employerBurdenStandard, preponderance of the evidence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerBurdenStandard Context triple: [Price Waterhouse v. Hopkins, employerBurdenStandard, preponderance of the evidence]
-
A.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
B.
laborSystem
Indicates the type or structure of work organization, employment arrangements, and labor relations that govern how work is performed and managed.
-
C.
eligibleWork
Indicates that a particular work satisfies the necessary conditions or criteria to qualify for a specified status, benefit, or consideration.
-
D.
laborProvision
Indicates the provision or supply of labor or workforce from one party to another for work or services.
-
E.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
- F. None of above. chosen
Provenance (4 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c5fd2c5c81909283b7a74aff89b7 |
completed | March 1, 2026, 11:04 p.m. |
Created at: March 1, 2026, 8 p.m.