# Should i accept it? **URL:** \ **Category:** Uncategorized\ **Tags:** usage, ner, solved\ **Created:** [April 24, 2019, 11:40pm UTC](https://support.prodi.gy/t/should-i-accept-it/1438 "2019-04-24T23:40:12Z")\ **Posts on this page:** 7\ **Page:** 1
**Author:** ![damiano](https://avatars.discourse-cdn.com/v4/letter/d/ebca7d/32.png) [@damiano](https://support.prodi.gy/u/damiano)\ **Post date:** [April 24, 2019, 11:40pm UTC](https://support.prodi.gy/t/should-i-accept-it/1438/1 "2019-04-24T23:40:13Z")
Hello, midnight dilemma 🙂 I am going to create a new corpus for a NER model that will recognize **organizations**. I have a db with many (\> 500k+) organizations names, so, basically i have created the relative patterns to then label them via prodigy. Now, i have a problem. Let’s suppose a company name like **ACME** and another name **ACME DIGITAL** My doubt is, should i ACCEPT the “ACME” suggestion if the sentence I am labelling has ACME DIGITAL ? ACME is a company, but, in that context i should also keep “DIGITAL” too. So the points are two: 1. if i accept ACME, does prodigy will never ask me again to label “acme digital” for other sentences? 2. if i reject it, does prodigy will never ask me to label companies with “ACME” word? Thank you! ---
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [April 25, 2019, 10:55am UTC](https://support.prodi.gy/t/should-i-accept-it/1438/2 "2019-04-25T10:55:40Z")
> [@damiano](#): > > if i accept ACME, does prodigy will never ask me again to label “acme digital” for other sentences? > if i reject it, does prodigy will never ask me to label companies with “ACME” word? The annotations you're collecting always refer to **this particular context**. So if the sentence is "He works at ACME DIGITAL" and Prodigy suggests you "ACME" as the `ORG` entity, you should always **reject** that. Otherwise, the feedback the model is getting is: "Yes, in this particular context, 'ACME' is `U-ORG` and all other conflicting spans (including 'ACME DIGITAL') are definitely incorrect." This is not what you want. By rejecting, you're telling the model "In this context, 'ACME' is _not_ a `U-ORG` entity. We know this. We don't know anything about the other possible analyses – it could be `B-ORG` and 'DIGITAL' could be `L-ORG`. So try again!" I actually have a segment about this exact question in my tips and tricks video: [![](https://img.youtube.com/vi/tMAU3gLbKII/hqdefault.jpg "FAQ #1: Tips & tricks for NLP, annotation & training with Prodigy and spaCy") ](https://www.youtube.com/watch?v=tMAU3gLbKII&t=214s) ---
**Author:** ![damiano](https://avatars.discourse-cdn.com/v4/letter/d/ebca7d/32.png) [@damiano](https://support.prodi.gy/u/damiano)\ **Post date:** [April 25, 2019, 2:33pm UTC](https://support.prodi.gy/t/should-i-accept-it/1438/3 "2019-04-25T14:33:29Z")
Thank you @ines ! I am going to see the video. However, is it correct to convert 500k organizations into patterns? should it will cause problem? (too much patterns?) ---
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [April 25, 2019, 3:14pm UTC](https://support.prodi.gy/t/should-i-accept-it/1438/4 "2019-04-25T15:14:27Z")
Ah, I missed that part. 500k is probably too much, yes. Do you have any frequency information about those organisations? Like, which of those are actually common and relevant, and which are not? For the patterns, you want to be focusing on names and examples that are more common, so you have a higher chance of finding those in context and annotate as many as possible. So maybe you’d want a few hundred or thousand patterns of the most common organisations. ---
**Author:** ![damiano](https://avatars.discourse-cdn.com/v4/letter/d/ebca7d/32.png) [@damiano](https://support.prodi.gy/u/damiano)\ **Post date:** [April 25, 2019, 10:55pm UTC](https://support.prodi.gy/t/should-i-accept-it/1438/5 "2019-04-25T22:55:59Z")
Ok @ines Could it be another approach to set the entities in the .jsonl directly and then confirm them via prodigy? could it works? Basically, pre-label the sentences before processing them via prodigy…and then just accept or reject. Maybe a custom recipe? ---
**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\ **Post date:** [April 26, 2019, 10:01am UTC](https://support.prodi.gy/t/should-i-accept-it/1438/6 "2019-04-26T10:01:01Z")
@damiano Yes, that’d work, too! This is pretty much what the `ner.match` recipe does – only that it generates the matches in the recipe and not in a pre-processing step. But if you have your own matching logic set up, pre-processing is actually pretty good, because you can do it once and then use one static file with the `mark` recipe to collect accept/reject annotations. ---
**Author:** ![damiano](https://avatars.discourse-cdn.com/v4/letter/d/ebca7d/32.png) [@damiano](https://support.prodi.gy/u/damiano)\ **Post date:** [April 26, 2019, 1:00pm UTC](https://support.prodi.gy/t/should-i-accept-it/1438/7 "2019-04-26T13:00:25Z")
That’s perfect! thank you so much @ines