Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Formats:
json
Sub-tasks:
document-retrieval
Languages:
English
Size:
1K - 10K
License:
File size: 1,369 Bytes
0e11747 830cdf4 0e11747 830cdf4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | {
"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
}
}
|