Four Decimal Places
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Four Decimal Places has 7 facts recorded in Dontopedia across 4 references, with 2 live disagreements.
Maturity scale
raw canonical shape-checked rule-derived certifiedRdf:typein disputerdf:type
- Formatting Specification[1]all time · B1c43907 80fa 4804 9f16 0edd887a0129
- Formatting Specification[2]all time · E439b65d D477 4a00 B619 B77ab784c2c2
- Numeric Format[3]all time · 80a16c0b 7043 48ab Aeb5 68a3a00737cb
- Numeric Format[4]sourceall time · C9baa714 Fb6f 4a4e A32c 8544bdaa25ed
Rdfs:labelin disputerdfs:label
Inbound 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.
usesFormatUses Format(4)
- Accuracy Log
ex:accuracy-log - F1 Log
ex:f1-log - Precision Log
ex:precision-log - Recall Log
ex:recall-log
formatsOutputFormats Output(1)
- Bleu Score Code
ex:bleu-score-code
formattedAsFormatted As(1)
- Latency
ex:latency
numberFormatNumber Format(1)
- Print Statement
ex:print-statement
specifiesSpecifies(1)
- Print Format
ex:print-format
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 (4)
- custom
ctx:claims/beam/b1c43907-80fa-4804-9f16-0edd887a0129- full textbeam-chunktext/plain1 KB
doc:beam/b1c43907-80fa-4804-9f16-0edd887a0129Show excerpt
# Calculate the BLEU score references = outputs.tolist() hypotheses = reformulated_outputs bleu_scores = [] for ref, hyp in zip(references, hypotheses): bleu_scores.append(sentence_bleu([ref.split()], hyp.split())) bleu_score = sum(b…
- custom
ctx:claims/beam/e439b65d-d477-4a00-b619-b77ab784c2c2- full textbeam-chunktext/plain1 KB
doc:beam/e439b65d-d477-4a00-b619-b77ab784c2c2Show excerpt
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') def calculate_metrics(y_true, y_pred): accuracy = accuracy_score(y_true, y_pred) precision = precision_score(y_true, y_pred, zero_division=…
- custom
ctx:claims/beam/80a16c0b-7043-48ab-aeb5-68a3a00737cb- full textbeam-chunktext/plain1012 B
doc:beam/80a16c0b-7043-48ab-aeb5-68a3a00737cbShow excerpt
expanded_query = ' '.join(expanded_query_parts) end_time = time.time() latency = end_time - start_time print(f"Expanded Query: {expanded_query}, Latency: {latency:.4f} seconds") return expanded_query # Test th…
- custom
ctx:claims/beam/c9baa714-fb6f-4a4e-a32c-8544bdaa25ed- full textbeam-chunktext/plain1 KB
doc:beam/c9baa714-fb6f-4a4e-a32c-8544bdaa25edShow excerpt
test_terms = ["term1", "term2", "term3"] * 500 # Thresholds to test thresholds = [0.8, .85, .9, .95] # Number of trials to average over num_trials = 10 # Dictionary to store precision results precision_results = {} for threshold in thre…
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