🤖 AI Drafted (Not reviewed)
Extract named entities (people, places, dates, organizations) from text
|
|
| Tool id |
extract_entities |
| Category |
llm |
| Uses a language model |
yes |
| Needs a generative model |
no |
| Runs over many items |
yes |
| Item handling |
elementwise |
| Structured output |
yes |
| Human-verified |
not yet |
What it reads
| Port |
Type |
Required |
What it is |
Text (text) |
text |
yes |
Text to extract entities from |
Context (context) |
any |
no |
Previous text/transcription |
Metadata (metadata) |
json |
no |
Existing metadata |
Documents (documents) |
json |
no |
Document metadata |
What it emits
| Port |
Type |
Required |
What it is |
Entities (entities) |
json |
— |
Extracted entities by category |
Text (text) |
text |
— |
Raw text response |
Value (value) |
any |
— |
Parsed value |
Texts (texts) |
array |
— |
Per-item texts |
Values (values) |
array |
— |
Per-item values |
Results (results) |
json |
— |
Full results |
Records (records) |
array |
— |
Per-document text records [{doc_id, text}, …]. |
Artifacts (artifacts) |
json |
— |
Artifact IDs |
Options
| Option |
Type |
Default |
What it does |
choices |
array |
— |
Valid choices. (Not shown in the editor.) |
chunk_size_chars |
integer |
0 |
Chunk large input text above this character budget (0=auto). |
deduplicate |
boolean |
yes |
Remove duplicates. |
entity_types |
array |
[“people”, “organizations”, “locations”, “dates”] |
Entity types. |
include_context |
boolean |
no |
Show context. |
match_mode |
string |
prefer |
Match mode. One of: prefer, strict, inform. |
max_items |
integer |
10 |
List max items. |
max_tokens |
integer |
8192 |
Max response. |
max_words |
integer |
50 |
Word limit. |
metadata_field |
string |
— |
Save to field. |
model_name |
string |
— |
Model name. |
output_format |
string |
text |
Response format. One of: text, boolean, choice, number, words, list, json. |
prompt |
string |
— |
Custom prompt. |
provider_name |
string |
— |
LLM provider. One of: openai, anthropic, google, ollama, lmstudio, groq, together, deepseek, mistral, openrouter, dashscope, xai, perplexity, fireworks, deepl. |
quality_gate |
boolean |
yes |
Stop the run if output is unreadable. |
reference_values |
object |
— |
Known values to match. (Not shown in the editor.) |
save_to_db |
boolean |
yes |
Save to library. |
save_to_file |
boolean |
no |
Export to file. |
temperature |
number |
0.7 |
Creativity. |
thinking_mode |
string |
off |
Chain-of-thought reasoning depth. One of: off, short, medium, long. |
The prompt it sends
This is what the tool asks a model, with every option left at its default. Changing the options above changes this text.
Extract named entities from the following text.
Entity types to extract:
- people: names of individuals, including full names and nicknames
- organizations: companies, institutions, agencies, groups
- locations: places, addresses, cities, countries, geographic features
- dates: dates, time periods, years, centuries
Return the results as valid JSON with entity types as keys and arrays of entities as values.
Example format:
{
"people": ["John Smith", "Jane Doe"],
"organizations": ["Acme Corp"],
"locations": ["New York", "Paris"],
"dates": ["January 1920", "1945"]
}
Return only valid JSON, no other text.