This article exposes critical flaws in Text-to-SQL benchmarks like BIRD and Spider. An audit of gold queries reveals that several contain incorrect joins, causing mathematically wrong results to be established as ground truth. Since standard execution accuracy measures performance by comparing outputs against these faulty reference answers, models are often penalized for being correct and rewarded for mimicking human errors. To address this, the author proposes a constraint-aware evaluation method that validates SQL logic against declared data semantics rather than relying on potentially incorrect gold results.
- Discrepancies between benchmark gold queries and database schema facts
- The inherent risks of using execution accuracy as the primary metric
- How annotation errors impact model rankings and enterprise deployments
- Introduction of constraint-aware evaluation to ensure semantic validity
- Discrepancies between benchmark gold queries and database schema facts
- The inherent risks of using execution accuracy as the primary metric
- How annotation errors impact model rankings and enterprise deployments
- Introduction of constraint-aware evaluation to ensure semantic validity
Agentic workflows are rapidly accelerating the volume of pull requests, and validation is quickly becoming the most critical bottleneck. Teams using service meshes like Istio are well-positioned to solve it in ephemeral environments.
Creating a JSON Schema for existing YAML values
We can infer a schema from existing YAML values and use it as a starting point when writing a new schema. The steps are:
Convert your values YAML file to JSON on https://www.json2yaml.com/
Paste the JSON on https://www.jsonschema.net/ and click on "Infer Schema"
Paste the schema into the values.schema.json file
W
We can infer a schema from existing YAML values and use it as a starting point when writing a new schema. The steps are:
Convert your values YAML file to JSON on https://www.json2yaml.com/
Paste the JSON on https://www.jsonschema.net/ and click on "Infer Schema"
Paste the schema into the values.schema.json file
W
var JSV = require("./jsv").JSV;
var json = {};
var schema = {"type" : "object"};
var env = JSV.createEnvironment();
var report = env.validate(json, schema);
if (report.errors.length === 0) {
//JSON is valid against the schema
}
var json = {};
var schema = {"type" : "object"};
var env = JSV.createEnvironment();
var report = env.validate(json, schema);
if (report.errors.length === 0) {
//JSON is valid against the schema
}
