Dontopedia

text

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

text has 33 facts recorded in Dontopedia across 16 references, with 4 live disagreements.

33 facts·5 predicates·16 sources·4 in dispute

Mostly:rdf:type(16), is used for(2), used for(2)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Inbound mentions (42)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

hasDataTypeHas Data Type(24)

hasTypeHas Type(6)

dataTypeData Type(2)

rdf:typeRdf:type(2)

usesTextTypeUses Text Type(2)

containsElementContains Element(1)

contrastsWithContrasts With(1)

ex:assignsValueEx:assigns Value(1)

hasFieldTypeHas Field Type(1)

hasPropertyTypeHas Property Type(1)

isAIs a(1)

Other facts (6)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

6 facts
PredicateValueRef
Is Used forTitle Field[9]
Is Used forContent Field[9]
Used forfull-text search[10]
Used forTerm Field[13]
Sub Type ofSearchable Type[1]
Contrasts WithKeyword Type[10]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

typebeam/a831412c-5b39-4f5e-bd4c-e51bc1e17cb2
ex:ElasticsearchDataType
labelbeam/a831412c-5b39-4f5e-bd4c-e51bc1e17cb2
text
subTypeOfbeam/a831412c-5b39-4f5e-bd4c-e51bc1e17cb2
ex:searchable-type
typebeam/2fce069a-0714-4bf1-b525-b39dea374779
ex:DataType
typeblah/omega/654
ex:DataType
typeblah/omega/726
ex:PostgresDataType
labelblah/omega/726
TEXT
typeblah/omega/883
ex:DataType
labelblah/omega/883
TEXT
typeblah/omega/892
ex:DataType
typebeam/84fdeb53-d371-40d5-a9d2-e745627f6849
ex:ElasticsearchFieldType
labelbeam/84fdeb53-d371-40d5-a9d2-e745627f6849
text
typebeam/8481d5cc-fb17-4c80-9a11-b145c8881707
ex:ElasticsearchFieldType
labelbeam/8481d5cc-fb17-4c80-9a11-b145c8881707
text
typebeam/1ec290c6-ad6c-4b29-a062-86f6f2dcd7f7
ex:DataType
labelbeam/1ec290c6-ad6c-4b29-a062-86f6f2dcd7f7
text
isUsedForbeam/1ec290c6-ad6c-4b29-a062-86f6f2dcd7f7
ex:title-field
isUsedForbeam/1ec290c6-ad6c-4b29-a062-86f6f2dcd7f7
ex:content-field
typebeam/5619af20-143e-4c8d-935d-7cde533deeed
ex:ElasticsearchFieldType
labelbeam/5619af20-143e-4c8d-935d-7cde533deeed
text
usedForbeam/5619af20-143e-4c8d-935d-7cde533deeed
full-text search
contrastsWithbeam/5619af20-143e-4c8d-935d-7cde533deeed
ex:keyword-type
typebeam/86e7afc6-a97c-4bd2-92ca-4b5128289493
ex:DataType
labelbeam/86e7afc6-a97c-4bd2-92ca-4b5128289493
text
typebeam/01eaccfb-7615-4204-98ea-bc544cdc2fbb
ex:FieldType
labelbeam/01eaccfb-7615-4204-98ea-bc544cdc2fbb
Text Field Type
typebeam/32482dcb-f293-412a-8ea0-a9dfc518165e
ex:FieldType
usedForbeam/32482dcb-f293-412a-8ea0-a9dfc518165e
ex:term-field
typebeam/009c923b-307a-4fea-925e-20fa07694470
ex:DataType
labelbeam/009c923b-307a-4fea-925e-20fa07694470
text
typebeam/35f6cc41-2be5-463a-be9c-95e4900404b7
ex:data-type
typebeam/cd6d461e-14b4-4068-995b-5892ec0a9962
ex:ElasticsearchDataType
labelbeam/cd6d461e-14b4-4068-995b-5892ec0a9962
text

References (16)

16 references
  1. ctx:claims/beam/a831412c-5b39-4f5e-bd4c-e51bc1e17cb2
    • full textbeam-chunk
      text/plain1 KBdoc:beam/a831412c-5b39-4f5e-bd4c-e51bc1e17cb2
      Show excerpt
      curl -X PUT "localhost:9200/my_index?pretty" -H 'Content-Type: application/json' -d' { "settings": { "number_of_shards": 5, "number_of_replicas": 1 }, "mappings": { "properties": { "field1"
  2. ctx:claims/beam/2fce069a-0714-4bf1-b525-b39dea374779
    • full textbeam-chunk
      text/plain1 KBdoc:beam/2fce069a-0714-4bf1-b525-b39dea374779
      Show excerpt
      - Use a managed service or deploy on a cloud provider to achieve the desired uptime. 2. **Define Schema**: - Define the schema for your vectors and metadata. 3. **Insert Vectors**: - Insert vectors into Weaviate using the appropr
  3. [3]6541 fact
    ctx:discord/blah/omega/654
    • full textomega-654
      text/plain1 KBdoc:agent/omega-654/3cf79eef-4d4b-4717-b755-d33c55a49b00
      Show excerpt
      [2025-12-05 23:31] omega [bot]: The key root cause blocking script storage is the missing `user_id` column in your `script_storage` table, causing the `CREATE_FAILED` error. I recommend a schema migration that adds at least the following t
  4. [4]7262 facts
    ctx:discord/blah/omega/726
    • full textomega-726
      text/plain3 KBdoc:agent/omega-726/e1255623-4cb2-42d3-8d14-cc640c00aa31
      Show excerpt
      [2025-12-13 13:49] foxhop.: Does that match ```#!/bin/bash # Create decision_logs table for append-only audit trail of bot decisions # Usage: ./create-decision-logs-table.sh set -e if [ -z "$DATABASE_URL" ] && [ -z "$POSTGRES_URL" ]; then
  5. [5]8832 facts
    ctx:discord/blah/omega/883
    • full textomega-883
      text/plain1 KBdoc:agent/omega-883/e6e56088-5a24-4d2c-bb6f-49ba1eeafad0
      Show excerpt
      [2026-01-17 04:26] omega [bot]: 🔧 20/30: pgCreateTable ✅ Success **Args:** ```json { "table": "user_profiles", "columns": [ { "name": "id", "type": "SERIAL", "nullable": false, "primaryKey": true, "uniq
  6. [6]8921 fact
    ctx:discord/blah/omega/892
    • full textomega-892
      text/plain2 KBdoc:agent/omega-892/306db621-b57b-49be-8743-5fce5b39fff2
      Show excerpt
      [2026-01-17 04:31] omega [bot]: Ah, you want the roast mode activated for anyone daring to invoke the sacred topic of antigravity? Got it. Prepare for a verbal thrashing worthy of someone defying the laws of physics with their logic: "Ah,
  7. ctx:claims/beam/84fdeb53-d371-40d5-a9d2-e745627f6849
    • full textbeam-chunk
      text/plain1 KBdoc:beam/84fdeb53-d371-40d5-a9d2-e745627f6849
      Show excerpt
      'mappings': { 'properties': { 'title': {'type': 'text'}, 'content': {'type': 'text'} } } }) # Index a document es.index(index='my_index', body={ 'title': 'Example Document', 'content'
  8. ctx:claims/beam/8481d5cc-fb17-4c80-9a11-b145c8881707
    • full textbeam-chunk
      text/plain1 KBdoc:beam/8481d5cc-fb17-4c80-9a11-b145c8881707
      Show excerpt
      mapping["mappings"]["properties"][field] = {"type": "text"} # Create the index with the defined mapping es.indices.create(index=index_name, body=mapping, ignore=400) def main(): corpus_path = 'path/to/corpus.csv'
  9. ctx:claims/beam/1ec290c6-ad6c-4b29-a062-86f6f2dcd7f7
  10. ctx:claims/beam/5619af20-143e-4c8d-935d-7cde533deeed
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5619af20-143e-4c8d-935d-7cde533deeed
      Show excerpt
      ### 4. **Exclude Unnecessary Fields** Exclude fields that are not frequently used in your searches. This can reduce the amount of data that needs to be loaded and processed. **Steps:** 1. Go to the index pattern in Kibana. 2. Click on the
  11. ctx:claims/beam/86e7afc6-a97c-4bd2-92ca-4b5128289493
    • full textbeam-chunk
      text/plain1 KBdoc:beam/86e7afc6-a97c-4bd2-92ca-4b5128289493
      Show excerpt
      # Create the index es.indices.create(index=index_name, body={ 'settings': { 'index': { 'number_of_shards': 1, 'number_of_replicas': 0 } }, 'mappings': { 'properties': {
  12. ctx:claims/beam/01eaccfb-7615-4204-98ea-bc544cdc2fbb
    • full textbeam-chunk
      text/plain1 KBdoc:beam/01eaccfb-7615-4204-98ea-bc544cdc2fbb
      Show excerpt
      - Use `refresh_interval` setting in the index settings. ### Example Configuration Here's an example of how you might configure your Elasticsearch index and queries for better performance: ```python from elasticsearch import Elasticsear
  13. ctx:claims/beam/32482dcb-f293-412a-8ea0-a9dfc518165e
    • full textbeam-chunk
      text/plain1 KBdoc:beam/32482dcb-f293-412a-8ea0-a9dfc518165e
      Show excerpt
      'track_total_hits': True # Enable total hits tracking }) print(response['hits']['total']['value']) # Output: 1 ``` #### 4. Hardware and Resource Allocation - **Ensure Sufficient Resources**: Allocate enough CPU, memory, and disk spa
  14. ctx:claims/beam/009c923b-307a-4fea-925e-20fa07694470
    • full textbeam-chunk
      text/plain1 KBdoc:beam/009c923b-307a-4fea-925e-20fa07694470
      Show excerpt
      - The `add_synonym` method adds a synonym to the dictionary, associating it with a specific term and context. 3. **Retrieving Synonyms**: - The `get_synonyms` method retrieves the synonyms for a given term and context. 4. **Rewritin
  15. ctx:claims/beam/35f6cc41-2be5-463a-be9c-95e4900404b7
    • full textbeam-chunk
      text/plain1 KBdoc:beam/35f6cc41-2be5-463a-be9c-95e4900404b7
      Show excerpt
      First, ensure that your Elasticsearch index is correctly configured with the synonym analyzer and filter. Your current configuration looks mostly correct, but there are a few improvements and checks we can make. ### 2. Use `synonyms_path`
  16. ctx:claims/beam/cd6d461e-14b4-4068-995b-5892ec0a9962

See also

Keep researching

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