Skip to main content
Glama

xcomet_batch_evaluate

Batch evaluate translation quality by processing multiple source-translation pairs to generate aggregate statistics and individual error analysis.

Instructions

Evaluate multiple translation pairs in a batch.

This tool processes multiple source-translation pairs and provides aggregate statistics along with individual results.

Args:

  • pairs (array): Array of translation pairs, each with:

    • source (string): Original source text

    • translation (string): Translated text

    • reference (string, optional): Reference translation

  • source_lang (string, optional): Source language code

  • target_lang (string, optional): Target language code

  • response_format ('json' | 'markdown'): Output format (default: 'json')

Returns: { "average_score": number, "total_pairs": number, "results": [ { "index": number, "score": number, "error_count": number, "has_critical_errors": boolean } ], "summary": string }

Examples:

  • Evaluate entire translated document

  • Compare MT system quality across test set

  • Identify segments needing attention

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pairsYesArray of translation pairs to evaluate
source_langNoSource language code
target_langNoTarget language code
response_formatNoOutput formatjson
use_gpuNoUse GPU for inference (faster if available). Default: false (CPU only)
batch_sizeNoBatch size for GPU processing (1-64). Larger = faster but uses more memory. Default: 8

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/shuji-bonji/xcomet-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server