end index
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
end index has 18 facts recorded in Dontopedia across 8 references, with 4 live disagreements.
Mostly:rdf:type(6), depends on(2), calculation(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (8)
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.
calculatesCalculates(3)
- Context Window Extraction Function
ex:context-window-extraction-function - Query Logic
ex:query-logic - Step 3
ex:step-3
usesUses(3)
- List Slicing
ex:list-slicing - Slicing Operation
ex:slicing-operation - Slicing Syntax
ex:slicing-syntax
usedInUsed in(1)
- Min Function
ex:min-function
usesEndIndexUses End Index(1)
- Slicing Operation
ex:slicing-operation
Other facts (17)
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 | Variable | [2] |
| Rdf:type | Variable | [3] |
| Rdf:type | Integer | [4] |
| Rdf:type | Integer | [5] |
| Rdf:type | Numeric Index | [7] |
| Rdf:type | Index Expression | [8] |
| Depends on | request.offset | [1] |
| Depends on | request.limit | [1] |
| Calculation | min(start_index + self.max_tokens, len(input_sequence)) | [3] |
| Calculation | start_index + self.max_tokens | [4] |
| Uses | Max Tokens | [4] |
| Uses | Input Sequence Length | [4] |
| Assigned From | query_request.offset + query_request.limit | [2] |
| Variable Name | end_index | [3] |
| Bounded by | len(input_sequence) | [4] |
| Type | integer | [5] |
| Formula | min(len(tokens),i+window_size+1) | [6] |
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 (8)
ctx:claims/beam/3ec50fdd-44d2-4d86-8a95-81a6108707be- full textbeam-chunktext/plain1 KB
doc:beam/3ec50fdd-44d2-4d86-8a95-81a6108707beShow excerpt
{"id": 2, "title": "Title 2", "content": "Content 2"}, ] @app.post("/query", response_model=QueryResponse) def query(request: QueryRequest): # Simulate querying the data store start = request.offset end = request.offset + r…
ctx:claims/beam/d525d9ae-20fb-4fd3-b227-e614fdb8138fctx:claims/beam/52d627ed-6239-49b6-bd14-efdba6a0d5cc- full textbeam-chunktext/plain1 KB
doc:beam/52d627ed-6239-49b6-bd14-efdba6a0d5ccShow excerpt
handler = logging.StreamHandler() formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') handler.setFormatter(formatter) self.logger.addHandler(handler) def segment_input(s…
ctx:claims/beam/e4c7f4cb-8e21-442a-8fff-67f9711c0bb0- full textbeam-chunktext/plain1 KB
doc:beam/e4c7f4cb-8e21-442a-8fff-67f9711c0bb0Show excerpt
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') handler.setFormatter(formatter) self.logger.addHandler(handler) def segment_input(self, input_sequence): """ …
ctx:claims/beam/d78a3311-25e6-4b90-ac75-59c6dfa59f13- full textbeam-chunktext/plain1 KB
doc:beam/d78a3311-25e6-4b90-ac75-59c6dfa59f13Show excerpt
self.logger = logging.getLogger(__name__) self.logger.setLevel(logging.INFO) handler = logging.StreamHandler() formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') han…
ctx:claims/beam/892c7b9e-a360-4951-a1bd-65dd1b7048dcctx:claims/beam/a7c1778b-c738-4750-8890-f115f9479040- full textbeam-chunktext/plain1 KB
doc:beam/a7c1778b-c738-4750-8890-f115f9479040Show excerpt
2. **Iterate Over Tokens**: We iterate over each token using a `for` loop. 3. **Calculate Context Window Indices**: For each token, we calculate the start and end indices for the context window, ensuring they stay within the bounds of the t…
ctx:claims/beam/7194b30d-2610-4c0a-ab28-89f65f718d7c- full textbeam-chunktext/plain1 KB
doc:beam/7194b30d-2610-4c0a-ab28-89f65f718d7cShow excerpt
def __init__(self): self.model = ReformulationModel() def process_queries(self, queries, batch_size=100, max_workers=10): with ThreadPoolExecutor(max_workers=max_workers) as executor: futures = [executor…
See also
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