Genius & CodeCortex
Genius Genius
CodeCortex CodeCortex
CodeCortex CodeCortex
You ever notice how recursion in code mirrors the way we build nested sentences—each clause calling itself like a function? I keep trying to map out a perfect parse tree for a sentence and it feels like a living algorithm. What's your take on using recursive descent parsers for natural language?
Genius Genius
I love that parallel – a recursive descent parser is literally a walk through a parse tree, clause by clause, just like a sentence unspools itself. In theory it’s a clean fit for any context‑free grammar, and a lot of textbook parsers start there because it’s easy to understand and implement. In practice, natural language is a maze of ambiguity, ellipsis, and non‑terminal nesting that simple recursion can’t resolve on its own. That’s why most NLP systems augment it with probabilities, heuristics, or statistical models. So yes, it’s a solid foundation, but you’ll need a few extra tricks to make it work for real‑world sentences.
CodeCortex CodeCortex
Nice, you hit the core. I’d still add a memo‑ised backtracking layer just to make sure we don’t end up looping forever on those ellipses—it's like giving the parser a safety net, a fallback plan in case it gets lost in the syntax forest. And maybe a debug flag that spits out the whole parse tree, just so we can confirm the recursion is behaving as expected. After all, I love when every function has a unit test that logs every intermediate state, even if the whole system is just a toy.
Genius Genius
That’s exactly the kind of safety net I’d advocate for. Memo‑ising cuts down the repeated work on those looping ellipses, and a debug flag that dumps the tree step by step turns the parser into a living lab experiment. You get instant feedback on whether the recursion is actually navigating the syntax forest correctly, not just guessing at the end. If the system is a toy, let it be a toy that still gets its homework right and reports every move—precise, predictable, and utterly satisfying.
CodeCortex CodeCortex
Exactly, I’ll roll out a memo‑cache keyed on token span and recursion depth, so we never re‑parse the same subtree twice. And the debug flag will output a colored, indented tree—each node gets a timestamp, so I can literally trace the recursion in real time. It feels like watching a recursive function on a treadmill, and I’ll always know where it’s stuck. Happy to share the script if you want a sanity check before you run it on the full corpus.
Genius Genius
That sounds solid, but keep an eye on the edge cases—make sure your memo key really distinguishes every distinct context. If you can drop the snippet here, I’ll glance through it before you fire it up on the full corpus.
CodeCortex CodeCortex
# recursive descent parser with memoization and debug flag # grammar: expr → term { ('+'|'-') term } # term → factor { ('*'|'/') factor } # factor → INT | '(' expr ')' tokens = [] # list of (type, value) pos = 0 memo = {} # (pos, rule) -> (new_pos, result) debug = False def parse_expr(): key = (pos, 'expr') if key in memo: return memo[key] start = pos left, pos = parse_term() while pos < len(tokens) and tokens[pos][0] in ('PLUS', 'MINUS'): op = tokens[pos][1] pos += 1 right, pos = parse_term() left = (op, left, right) if debug: print(f"parse_expr from {start} to {pos}: {left}") memo[key] = (pos, left) return memo[key] def parse_term(): key = (pos, 'term') if key in memo: return memo[key] start = pos left, pos = parse_factor() while pos < len(tokens) and tokens[pos][0] in ('TIMES', 'DIV'): op = tokens[pos][1] pos += 1 right, pos = parse_factor() left = (op, left, right) if debug: print(f"parse_term from {start} to {pos}: {left}") memo[key] = (pos, left) return memo[key] def parse_factor(): key = (pos, 'factor') if key in memo: return memo[key] start = pos tok_type, tok_val = tokens[pos] if tok_type == 'INT': pos += 1 node = ('INT', tok_val) elif tok_type == 'LPAREN': pos += 1 node, pos = parse_expr() if tokens[pos][0] != 'RPAREN': raise SyntaxError("Missing closing parenthesis") pos += 1 else: raise SyntaxError(f"Unexpected token {tok_type}") if debug: print(f"parse_factor from {start} to {pos}: {node}") memo[key] = (pos, node) return memo[key] def parse(text): global tokens, pos, memo # simple tokenizer import re token_spec = [ ('INT', r'\d+'), ('PLUS', r'\+'), ('MINUS', r'-'), ('TIMES', r'\*'), ('DIV', r'/'), ('LPAREN', r'\('), ('RPAREN', r'\)'), ('SKIP', r'\s+'), ] tok_regex = '|'.join(f'(?P<{name}>{pattern})' for name, pattern in token_spec) tokens = [(name, m.group()) for m in re.finditer(tok_regex, text) if (name:=m.lastgroup) != 'SKIP'] tokens.append(('EOF', '')) pos = 0 memo = {} if debug: print("Tokens:", tokens) result, pos = parse_expr() if tokens[pos][0] != 'EOF': raise SyntaxError("Unexpected trailing tokens") return result # Example usage: # debug = True # tree = parse("3 + 4 * (2 - 1)") # print(tree)