They need to be able to match the

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Content in their index with your search query based on the meaning of both. However challenging this may sound already, it’s just the beginning. Many searches are unintentionally ambiguous Around 40% of English words are polysemous—they have two or more meanings. It’s arguably the most significant challenge that semantic search is trying to solve. For example, the keyword “python” has 533,000 monthly searches in the US alone: python search volume 1 If I were to ever search for “python,” I’d most likely be referring to the programming language. But anyone outside of the tech industry would likely expect the actual snake or the legendary British comedy troupe. The problem here is that words rarely have a definitive meaning without context.


On top of the polysemous words, you have countless nouns that can also be adjectives, verbs, or both. And we’re still in the scope Special Data of literal meanings. It gets even more interesting if we delve into inferred meanings (think sarcasm). Context is everything in semantics, and it brings us to the remaining two points. The need to understand lexical hierarchy and entity relationships Let’s take a look at the following search query and the top search result: complex query example 1 That’s truly impressive. Here’s what Google has to do to understand this query: Know that “partner” means wife/girlfriend/husband/boyfriend/spouse. Understand that Obi-Wan appeared in multiple movies and series played by different actors.




Make the connections. Display search results in a way that reflects the ambiguity of “obi wan.” I can’t even imagine what kind of search results I’d get if I did that search in 2010 or earlier. Now, let’s take a step back to explain the concepts. Lexical hierarchy illustrates the relationship between words. The word partner is superordinate (hypernym) to wife, boyfriend, spouse, and others. As mentioned earlier, our queries often don’t match the exact wording of the desired content. Knowing that “affordable” is anything between cheap, mid-range, and reasonably priced is crucial. Entities, in this example, are movie and series characters (Obi-Wan), people with a specific job (actor), and people who are associated with them (partners).