search
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
search has 11 facts recorded in Dontopedia across 5 references, with 2 live disagreements.
Mostly:rdf:type(3), has argument(2), belongs to many(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (5)
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.
callsCalls(2)
- Search Function
ex:search-function - Search Reformulated Query Function
ex:search-reformulated-query-function
callsMethodCalls Method(1)
- Search Reformulated Query Function
ex:search-reformulated-query-function
isImplementedByIs Implemented by(1)
- Search Operation
ex:search-operation
usesMethodUses Method(1)
- Code Snippet 1
ex:code-snippet-1
Other facts (10)
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.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Method | [1] |
| Rdf:type | Elasticsearch Api Function | [2] |
| Rdf:type | Elasticsearch Method | [4] |
| Has Argument | Index Name Arg | [1] |
| Has Argument | Body Arg | [1] |
| Belongs to Many | Elasticsearch Client | [3] |
| Called on | Es Variable | [4] |
| Has Index | reformulated_queries | [4] |
| Has Query | Match Query | [4] |
| Targets Index | reformulated_queries | [5] |
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.
References (5)
ctx:claims/beam/b5d9ecaf-e81d-404e-b6ba-4ff3bc636accctx:claims/beam/e3462606-2a58-4967-b7c7-2170e53b40d6- full textbeam-chunktext/plain1 KB
doc:beam/e3462606-2a58-4967-b7c7-2170e53b40d6Show excerpt
response = es.search(index="test_index", body=query) print(response) ``` What are some strategies for scaling the Elasticsearch cluster to handle a large number of records? ->-> 1,15 [Turn 9913] Assistant: Designing a scalable architecture…
ctx:claims/beam/dc43e263-ae12-4ebe-aaee-b46ef58b17d0- full textbeam-chunktext/plain1 KB
doc:beam/dc43e263-ae12-4ebe-aaee-b46ef58b17d0Show excerpt
'settings': { 'analysis': { 'analyzer': { 'synonym_analyzer': { 'type': 'custom', 'tokenizer': 'standard', 'filter': ['synonym_filter'] …
ctx:claims/beam/5a187c47-fa54-48fc-b754-00d1a5a7c6f3- full textbeam-chunktext/plain1 KB
doc:beam/5a187c47-fa54-48fc-b754-00d1a5a7c6f3Show excerpt
from elasticsearch import Elasticsearch # Initialize Elasticsearch client es = Elasticsearch([{'host': 'localhost', 'port': 9200}]) def index_reformulated_query(query, reformulated_query): # Index the reformulated query es.index(i…
ctx:claims/beam/aa945c3d-7515-4683-8a1c-ba06089b9a9e- full textbeam-chunktext/plain1 KB
doc:beam/aa945c3d-7515-4683-8a1c-ba06089b9a9eShow excerpt
("Book a flight to New York", "Reserve a ticket to New York City"), ("How do I get to the airport?", "Provide directions to the airport") ] for original_query, reformulated_query in test_queries: index_reformulated_query(origin…
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