实现EARLEY 算法，要代码

EARLEY算法是一种用于解析上下文无关文法的算法，它可以在任意阶段发现句法错误。下面是简单的Python代码实现一个基本的Earley分析器：

class GrammarRule:
    def __init__(self, left, right):
        self.left = left
        self.right = right

class Item:
    def __init__(self, symbol, index=0):
        self.symbol = symbol
        self.index = index

class EarleyParser:
    def __init__(self, grammar, sentence):
        self.grammar = grammar
        self.sentence = sentence
        self.items = self._build_initial_items()

    def _build_initial_items(self):
        items = []
        for rule in self.grammar.nonterminals:
            if rule == '$':
                continue
            for i in range(len(self.sentence) + 1):
                items.append(Item(rule, i))
        return items

    def parse(self):
        completed = set()
        while True:
            new_completed = set()
            for item in self.items:
                if not item.is_complete():
                    # 扫描过程
                    next_symbols = self._get_next_symbols(item)
                    for sym, dot_index in next_symbols:
                        new_item = Item(item.symbol, item.index + 1)
                        new_item.dot = dot_index
                        if sym not in completed:
                            self.items.append(new_item)
                        else:
                            completed.add((item.symbol, sym, dot_index))
                else:
                    new_completed.add(item)
            if len(completed) == len(self.items):
                break
            self.items = list(completed)

        result = []
        for item in self.items:
            if item.symbol == '$':
                result.extend(self._parse_sentence(item, self.sentence))
        return result

    def _get_next_symbols(self, item):
        symbols = []
        current_rule = self.grammar.rules[item.symbol]
        for r in current_rule.right:
            if isinstance(r, str):
                symbols.append((r, item.index))
            elif isinstance(r, tuple):
                for i in range(item.index, len(self.sentence) + 1):
                    symbols.append((r[0], i))
        return symbols

    def _parse_sentence(self, item, sentence):
        result = []
        for sym, dot_index in self._get_next_symbols(item):
            sub_result = self.parse()[0]  # 假设只有一个项目可以完成
            if sub_result is not None:
                result.append(sub_result)
        return result

# 使用示例
grammar = {
    'S': ['NP', 'VP'],
    'NP': [['Det', 'N'], ('$',)],
    'VP': [['V', 'NP'], ('$',)],
    'Det': ['a', 'an'],
    'N': ['cat', 'dog', 'table'],
    'V': ['run', 'jump'],
}

sentence = 'the cat runs'.split()
parser = EarleyParser(grammar, sentence)
print(parser.parse())

这个版本的Earley解析器实现了基本的扫描和预测步骤。注意这只是一个简化版的实现，实际应用中可能需要处理更复杂的情况，比如错误处理、优化等。