You will be shown an abstract from a computer science research paper. Given this abstract, your task is to extract all unique entities with the following types:

- "Task": Applications, problems to solve, systems to construct. Examples include "information extraction", "machine reading system", "image segmentation".
- "Method": : Methods, models, systems to use, or tools, components of a system, frameworks. Examples include "language model", "CORENLP", "POS parser".
- "Metric": Metrics, measures, or entities that can express quality of a system / method. Examples include "F1", "BLEU", "Precision", "time complexity".
- "Material": Data, datasets, resources, Corpus, Knowledge base. Examples include "image data", "speech data", "stereo images", "CoNLL", "Wikipedia".
- "OtherScientificTerm": Phrases that are a scientific terms but do not fall into any of the above classes. Examples include "physical or geometric constraints", "qualitative prior knowledge", "tree kernel", "noise".
- "Generic": General terms or pronouns that may refer to a entity but are not themselves informative, often used as connection words. Examples include "model", "approach", "them".

Please return the output as a JSON object of the format: {"type1" : ["example_entity", ...], "type2" : ["example_entity", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. Entity types with no matching entities should be assigned an empty array [].

For instance, the output might look like: {"Task": ["speech recognition", ...], "Method": ["Conditional random field"], "Material": [], ...}.

Only output the JSON object and do not include any additional text.

Abstract:

This paper summarizes the formalism of Category Cooccurrence Restrictions (CCRs) and describes two parsing algorithms that interpret it. CCRs are Boolean conditions on the cooccurrence of categories in local trees which allow the statement of generalizations which can not be captured in other current syntax formalisms. The use of CCRs leads to syntactic descriptions formulated entirely with restrictive statements. The paper shows how conventional algorithms for the analysis of context free languages can be adapted to the CCR formalism. Special attention is given to the part of the parser that checks the fulfillment of logical well-formedness conditions on trees.
{"Generic": ["it"], "Material": ["context free languages"], "Method": ["parsing algorithms", "syntax formalisms"], "Metric": [], "OtherScientificTerm": ["local trees", "syntactic descriptions", "Category Cooccurrence Restrictions (CCRs)", "restrictive statements", "logical well-formedness conditions", "trees", "statement of generalizations", "Boolean conditions"], "Task": ["formalism of Category Cooccurrence Restrictions (CCRs)"]}