哪个更好？ OpenCyc 还是 ConceptNet？
我正在做一个 NLP 项目，我需要识别句子中的概念以找到其他类似的概念。我这样做是为了从已有的列表中推断单词的价数。我开始使用 WordNet，但它给出了许多矛盾的结果。我所说的矛盾结果是指具有矛盾价的词扩展。
所以现在我正在研究 ConceptNet 和 OpenCyc。我已经实现了 ConceptNet，一切都非常简单，我喜欢它。问题是 OpenCyc 似乎有一个更大、逻辑上更严格的数据库，当我在 WordNet 上发现这么多“矛盾”时，这一点很重要......但我不知道，因为我还没有尝试过。
有人可以告诉我是否值得付出（对我来说相当大的）努力来实现 OpenCyc，或者 ConceptNet 是否足以推断词价？他们有那么不同吗？
如果需要的话，我很乐意进一步解释自己。现在尽量保持简短！
谢谢！
I'm doing a NLP project where I need to recognise concepts in sentences to find other similar concepts. I do this to infer word valences from a list I already have. I started using WordNet, but it gave many contradictory results. By contradictory results I mean word expansions that had contradictory valences.
So now I'm looking into ConceptNet and OpenCyc. I've already implemented ConceptNet and it was all very easy and I love it. Problem is that OpenCyc appears to have a much larger and more logically rigid database, which is important when I found so many "contradictions" on WordNet... But I wouldn't know because I haven't tried it.
Could someone tell me if it's worth going through the (considerable, for me) effort to implement OpenCyc, or is ConceptNet good enough to infer word valences? Are they that different?
I'll be happy to explain myself further, if needed. Trying to keep it short for now!
Thanks!
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这不值得付出努力。 ConceptNet 更好、更容易处理。
当我使用 ConceptNet 时，只需下载一个 sqlite 数据库和一个 python 模块来访问其中的关系。对于 OpenCyc 来说，这是一个更大的下载，并且必须通过 Web 服务器进行设置，该服务器需要很长时间才能加载并使用大量内存。从那以后事情可能发生了变化，但这是我的经历。
It's not worth the effort. ConceptNet is heaps better and easier to deal with.
When I used ConceptNet, it was a matter of downloading a sqlite database and a python module to access the relations in it. For OpenCyc, it was a bigger download, and had to be set up through a web server that took ages to load and used enormous amounts of memory. Things may have changed since, but this was my experience.