<p>You might be referring to <a href="https://en.wikipedia.org/wiki/Semantic_role_labeling" rel="nofollow noreferrer"><strong>Semantic role labeling</strong></a>. SRL is the task of assigning labels to words or phrases in a sentence that shows their semantic role in that sentence. </p>

<p>In your example <code>CV was hit by IV</code>, the task is to identify the verb "hit" carried out by the <code>actor</code> "CV" affected "IV" the <code>recipient</code>.</p>

<p>Note: If you're only interested in the syntactic relationship among words or phrases in a sentence, not the semantic relationship between them, simple <strong>dependency parsing</strong> would do the job.</p>

CC BY-SA 4.0
2018-09-25T09:03:37.953Z
2018-09-25T09:03:37.953Z
ngub05
<p>Within a piece of text, I'm trying to detect who did what to whom.</p>
<p>For instance, in the following sentences:</p>
<blockquote>
<p>CV hit IV. CV was hit by IV.</p>
</blockquote>
<p>I'd like to know who hit whom.</p>
<p>I can't remember what this technique is called.</p>

<natural-language-processing><reference-request><computational-linguistics>
What is the name of the NLP technique that determines "who did what to whom" given a sentence?
tmthyjames
# What is the name of the NLP technique that determines "who did what to whom" given a sentence?

(Asked by: username_0 on 2018-09-24)

Within a piece of text, I'm trying to detect who did what to whom.

For instance, in the following sentences:

> CV hit IV. CV was hit by IV.

I'd like to know who hit whom.

I can't remember what this technique is called.

**Tags:** natural-language-processing, reference-request, computational-linguistics


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## 1 answers

### Answer by username_1 on 2018-09-25. Score: 3 | Accepted answer

You might be referring to [**Semantic role labeling**](https://en.wikipedia.org/wiki/Semantic_role_labeling). SRL is the task of assigning labels to words or phrases in a sentence that shows their semantic role in that sentence.

In your example `CV was hit by IV`, the task is to identify the verb "hit" carried out by the `actor` "CV" affected "IV" the `recipient`.

Note: If you're only interested in the syntactic relationship among words or phrases in a sentence, not the semantic relationship between them, simple **dependency parsing** would do the job.


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