Add 'brainsteam/content/replies/2022/11/23/1669234351.md'

brainsteam/content/replies/2022/11/23/1669234351.md

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+---
+date: '2022-11-23T20:12:31'
+hypothesis-meta:
+  created: '2022-11-23T20:12:31.341810+00:00'
+  document:
+    title:
+    - 2210.07188.pdf
+  flagged: false
+  group: __world__
+  hidden: false
+  id: KRvuAmtrEe26TOOrc3o_zA
+  links:
+    html: https://hypothes.is/a/KRvuAmtrEe26TOOrc3o_zA
+    incontext: https://hyp.is/KRvuAmtrEe26TOOrc3o_zA/arxiv.org/pdf/2210.07188.pdf
+    json: https://hypothes.is/api/annotations/KRvuAmtrEe26TOOrc3o_zA
+  permissions:
+    admin:
+    - acct:ravenscroftj@hypothes.is
+    delete:
+    - acct:ravenscroftj@hypothes.is
+    read:
+    - group:__world__
+    update:
+    - acct:ravenscroftj@hypothes.is
+  tags:
+  - data-annotation
+  - coreference
+  - NLProc
+  target:
+  - selector:
+    - end: 26459
+      start: 26292
+      type: TextPositionSelector
+    - exact: 'an algorithm with high precision on LitBank orOntoNotes would miss a
+        huge percentage of rele-vant mentions and entities on other datasets (con-straining
+        our analysis) '
+      prefix: re mentions of differentlengths.
+      suffix: and when annotating newtexts and
+      type: TextQuoteSelector
+    source: https://arxiv.org/pdf/2210.07188.pdf
+  text: these datasets have the most limited/constrained definitions for co-reference
+    and what should be marked up so it makes sense that precision is poor in these
+    datasets
+  updated: '2022-11-23T20:12:31.341810+00:00'
+  uri: https://arxiv.org/pdf/2210.07188.pdf
+  user: acct:ravenscroftj@hypothes.is
+  user_info:
+    display_name: James Ravenscroft
+in-reply-to: https://arxiv.org/pdf/2210.07188.pdf
+tags:
+- data-annotation
+- coreference
+- NLProc
+- hypothesis
+type: reply
+url: /replies/2022/11/23/1669234351
+
+---
+
+
+
+ <blockquote>an algorithm with high precision on LitBank orOntoNotes would miss a huge percentage of rele-vant mentions and entities on other datasets (con-straining our analysis) </blockquote>these datasets have the most limited/constrained definitions for co-reference and what should be marked up so it makes sense that precision is poor in these datasets