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Sentor Sentiment Analysis

AI-powered sentiment analysis for text documents

Document → Predict Sentiment

AI-generated

Summary

Send each incoming document’s text and entity list to Sentor for sentiment analysis in the selected language and environment. Return one result per successfully matched document, either as a simplified sentiment record or the full API result.

Inputs

  • Environment — Select Production (default) or Development Sentor API.
  • Language — Choose English (default) or Dutch for analysis.
  • Document Text (required) — Text to analyze for each input item. Blank text causes an item error.
  • Document ID — Optional identifier for the document; if omitted or empty, an ID such as doc_0 is generated.
  • Entities (required) — At least one entity name to analyze within each document. Values are trimmed and deduplicated; an empty list causes an item error.
  • Simplify Output — Defaults to true. When enabled, return predicted_class, predicted_label, the probability for that label (or 0 if absent), and details. When disabled, return the full result object from Sentor.

Output shape

A list of items, typically one per input document.

The node batches valid input documents into one API request, then matches returned results by document ID. With Continue On Fail enabled, per-item validation failures and request or result errors are returned as items with an error field; otherwise errors are thrown. If no documents pass validation, no API request is made.

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