WNUT 2020 Shared Task-1: Conditional Random Field( CRF ) based Named Entity Recognition( NER ) for Wet Lab Protocols (2020)

Abstract: The paper describes how classifier model built using Conditional Random Field detects named entities in wet lab protocols.

## introduction wet laboratories are laboratories for conducting biology and chemistry experiments. these require handling of various types of chemicals and potential "wet" hazards. these experiments are guided by a sequence of instructions collectively referred as wet lab protocols. the instructions are mostly composed of imperative statements which are meant to describe an action. figure 1 shows a representative wet lab protocol. figure 2 shows brat annotations (entities and relations) on two sentences from the representative protocol. for each protocol, annotators had identified and marked every span of text corresponding to action or one of the 17 types of entities. standard rna synthesis (e2050) thaw the necessary kit components. mix and pulse-spin in microfuge to collect solutions to the bottoms of tubes. keep on ice. assemble the reaction at room temperature in the following order:. mix thoroughly and pulse-spin in a microfuge. incubate at 37c for 2 hours. optional step: dnase treatment to remove dna template. to remove template dna, add 30 l nuclease-free water to each 20 l reaction, followed by 2 l of dnase i (rnase-free), mix and incubate for 15 minutes at 37c. proceed with purification of synthesized rna or analysis of transcription products by gel electrophoresis. named entity recognition (ner) aims at identifying these entities within a given protocol. ## named entity recognition methodology a conditional random fields (crf) classifier was trained to recognize named entities. the crf ner model was implemented using sklearn-crfsuite 2 which is a python wrapper over c++ based crfsuite 3 . it utilized l-bfgs @xcite , a limited memory quasi-newton algorithm for large scale numerical optimization. the classifier was trained with both l1 and l2 regularization. ## experiments the experiments were based on the datasets provided by the organizers of w-nut 2020 shared task on entity and relation recognition over wet lab protocols @xcite . the dataset ( ## conclusion this paper has proposed a crf-based named entity extraction system to extract action and 17 entities of wet lab protocols. future plan: