LAC2.0.4版本mode=rank分析结果没有重要性信息

lac = LAC(mode='rank')

texts = [u"LAC是个优秀的分词工具", u"百度是一家高科技公司"]

rank_result = lac.run(texts)

结果如下：
rank_result = [
(['LAC', '是', '个', '优秀', '的', '分词', '工具'],
[nz, v, q, a, u, n, n]),
(['百度', '是', '一家', '高科技', '公司'],
[ORG, v, m, n, n])
]

找不到 [3, 0, 2, 3, 1] 这样的信息

Start at the LAC(mode='rank') API entry point and reproduce the example with the supplied texts. Trace how the rank result is assembled and determine where the importance information is lost; done means the result includes the expected importance values alongside the tokens and tags.

Written by the indexing model from the issue text.