Finding Textual Exact Duplicates
If you're a Relativity admin, here's how to go about finding exact text duplicates.
1. Create a fixed length field with 255 characters.
![](https://static.wixstatic.com/media/af7fa4_e92a698e6e034ff09e2710b63a054a74~mv2.png/v1/fill/w_85,h_55,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_e92a698e6e034ff09e2710b63a054a74~mv2.png)
2. In the Relational Field Properties section of the new field form, set the field to be relational, import blank values unchanged, and select the 'Textual Near Duplicates Relational View'.
![](https://static.wixstatic.com/media/af7fa4_c507589999fb42b980c43ad1aa6bce31~mv2.png/v1/fill/w_49,h_7,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_c507589999fb42b980c43ad1aa6bce31~mv2.png)
3. Save the field.
4. Under Indexing & Analytics, select Structured Analytics Set, then click, 'New Structured Analytics Set'
![](https://static.wixstatic.com/media/af7fa4_562bb658e2b24cafbead7425aaf52e2f~mv2.png/v1/fill/w_90,h_29,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_562bb658e2b24cafbead7425aaf52e2f~mv2.png)
5. Enter a name and prefix, choose a saved search as the document set, and then check off "Textual near duplicate identification" as the operation.
![](https://static.wixstatic.com/media/af7fa4_a0f715e39d8e47a593805746eed343d8~mv2.png/v1/fill/w_90,h_46,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_a0f715e39d8e47a593805746eed343d8~mv2.png)
6. Set the minimum similarity percentage to 100, then in the 'Destination Textual Near Duplicate Group' select the new field you created.
![](https://static.wixstatic.com/media/af7fa4_090f12c095594e12a444c781a9f5683b~mv2.png/v1/fill/w_83,h_36,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_090f12c095594e12a444c781a9f5683b~mv2.png)
7. Save and then in the console on the right click, 'Run Structured Analytics'.
![](https://static.wixstatic.com/media/af7fa4_c380e715129c4aa2ade8c177ad1dd434~mv2.png/v1/fill/w_118,h_172,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_c380e715129c4aa2ade8c177ad1dd434~mv2.png)
8. You'll be give the option to either update all of the documents, or just new documents added to the set.
![](https://static.wixstatic.com/media/af7fa4_cf6ec2de65a9448b8bc8653ad878bec6~mv2.png/v1/fill/w_84,h_37,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_cf6ec2de65a9448b8bc8653ad878bec6~mv2.png)
![](https://static.wixstatic.com/media/af7fa4_e39cfde67dff46f8a4601bfb8383d19b~mv2.png/v1/fill/w_85,h_37,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_e39cfde67dff46f8a4601bfb8383d19b~mv2.png)
9. In this example, the summary at the end indicates that 40 exact textual duplicates were found.
![](https://static.wixstatic.com/media/af7fa4_a4b0d6be9fdd42c3bd3753c9802c5465~mv2.png/v1/fill/w_83,h_40,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_a4b0d6be9fdd42c3bd3753c9802c5465~mv2.png)
10. So in this example we can see that there are three duplicates of CTRL0000001186.0001, which is given as the group ID for all four. A separate Yes/No field, 'X617: Textual Near Duplicate Principal' indicates which document is the anchor for the others.
![](https://static.wixstatic.com/media/af7fa4_7245674bbb694a61955582324a3ff1e1~mv2.png/v1/fill/w_49,h_14,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/af7fa4_7245674bbb694a61955582324a3ff1e1~mv2.png)