dataset_info.json

{
  "builder_name": "ParseEmbed",
  "config_name": "default",
  "dataset_name": "ParseEmbed",
  "dataset_size": 720,
  "description": "A hard retrieval benchmark for embedding models covering meaning, formatting, and table grounding.",
  "license": "apache-2.0",
  "version": {
    "version_str": "0.1.0",
    "major": 0,
    "minor": 1,
    "patch": 0
  },
  "task_categories": [
    "text-retrieval"
  ],
  "task_ids": [
    "document-retrieval"
  ],
  "annotations_creators": [
    "algorithmic"
  ],
  "multilinguality": "monolingual",
  "source_datasets": [
    "original"
  ],
  "language": [
    "en"
  ],
  "pretty_name": "ParseEmbed",
  "size_categories": [
    "n<1K"
  ],
  "tags": [
    "benchmark",
    "evaluation",
    "text",
    "retrieval",
    "hard-negatives",
    "table-retrieval"
  ],
  "author": "Convence",
  "features": {
    "query-id": {
      "dtype": "string",
      "_type": "Value"
    },
    "corpus-id": {
      "dtype": "string",
      "_type": "Value"
    },
    "score": {
      "dtype": "int64",
      "_type": "Value"
    }
  },
  "splits": {
    "test": {
      "name": "test",
      "num_examples": 720,
      "dataset_name": "ParseEmbed"
    }
  },
  "parseembed": {
    "benchmark_config": "parse-embed",
    "benchmark_splits": [
      "mean",
      "text_formatting",
      "table"
    ],
    "corpus_documents": 2880
  }
}