shorten README

README.md

@@ -1,4 +1,4 @@
-# ZOE (Zero-shot Open Typing)
+# ZOE (Zero-shot Open Entity Typing)
 A state of the art system for zero-shot entity fine typing with minimum supervision
 
 ## Introduction
@@ -7,118 +7,57 @@ This is a demo system for our paper "Zero-Shot Open Entity Typing as Type-Compat
 which at the time of publication represents the state-of-the-art of zero-shot entity typing.
 
 The original experiments that produced all the results in the paper
-are done with a package written in Java. This is a re-written package 
-that contains the same core, without experimental code. It's solely for
+are done with a package written in Java. This is a re-written package solely for
 the purpose of demoing the algorithm and validating key results. 
 
-The results may slightly differ from published numbers, due to the randomness in Java's 
-HashSet and Python set's iteration order. The difference should be within 0.5%.
+The results may be slightly different with published numbers, due to the randomness in Java's 
+HashSet and Python set's iteration order. The difference should be negligible.
 
-A major flaw of this system is the speed of running new sentences, due to ELMo processing.
-We have cached ELMo results for the provided experiments to make running experiments possible.
+This system may take a long time if ran on a large number of new sentences, due to ELMo processing.
+We have cached ELMo results for the provided experiments.
 
-To this end, we are working on an online demo, and we plan to release it before EMNLP 2018.
+The package also contains an online demo, please refer to [Publication Page](http://cogcomp.org/page/publication_view/845)
+for more details.
 
 ## Usage
 
 ### Install the system
 
 #### Prerequisites
 
-* Minimum 16G available disk space and 16G memory. (Lower specs will not work)
+* Minimum 20G available disk space and 16G memory. (strict requirement)
 * Python 3.X (Mostly tested on 3.5)
-* A POSIX OS (Windows not tested)
+* A POSIX OS (Windows not supported)
 * Java JDK and Maven
-* `virtualenv` if you are installing with script (check if `virtualenv` command works)
+* `virtualenv` if you are installing with script
 * `wget` if you are installing with script (Use brew to install it on OSX)
 * `unzip` if you are installing with script
 
-#### Install using a shell script
+#### Install using a one-line command
 
-To make everyone's life easier, we have provided a simple way for install, simply run `sh install.sh`.
+To make life easier, we provide a simple way to install with `sh install.sh`.
 
 This script does everything mentioned in the next section, plus creating a virtualenv. Use `source venv/bin/activate` to activate.
 
 #### Install manually
 
-Generally it's recommended to create a Python3 virtualenv and work under it.
-
-You need to first install AllenAI's bilm-tf package by running `python3 setup.py install` in ./bilm-tf directory
-
-Then install requirements by `pip3 install -r requirements.txt` in project root
-
-Then you need to download all the data/model files. There are two steps in this:
-* in bilm-tf/, download [model.zip](http://cogcomp.org/Data/ccgPapersData/xzhou45/zoe/model.zip), and uncompress
-* project root, download [data.zip](http://cogcomp.org/Data/ccgPapersData/xzhou45/zoe/data.zip), and uncompress
-
-Then check if all files are here by `python3 scripts.py CHECKFILES` or `python3 scripts.py CHECKFILES figer`
-in order to check figer caches etc.
+See wiki [manual-installation](https://github.com/CogComp/zoe/wiki/Manual-Installation)
 
 ### Run the system
 
-Currently you can do the following:
+Currently you can do the following without changes to the code:
 * Run experiment on FIGER test set (randomly sampled as the paper): `python3 main.py figer`
 * Run experiment on BBN test set: `python3 main.py bbn`
 * Run experiment on the first 1000 Ontonotes_fine test set instances (due to size issue): `python3 main.py ontonotes`
 
-Additionally, you can run server mode that initializes an online demo with `python3 server.py`
-However, this requires some additional file that's not provided for download yet.
+Additionally, you can run server mode that initializes the online demo with `python3 server.py`
+However, this requires some additional files that's not provided for download yet.
 Please directly contact the authors.
 
-It's generally an expensive operation to run on new sentences, but you can still do it.
-Please refer to `main.py` to see how you can test on your own data. 
-
-## Engineering details
-
-### Structure
-
-The package is composed with 
-
-* A slightly modified ELMo source code, see [bilm-tf](https://github.com/allenai/bilm-tf)
-* A main library `zoe_utils.py`
-* A executor `main.py`
-* A script helper `script.py` 
-
-### zoe_utils.py
-
-This is the main library file which contains the core logic.
-
-It has 4 main component Classes:
-
-#### `EsaProcessor`
-
-Supports all operations related to ESA and its data files. 
-
-A main entrance is `EsaProcessor.get_candidates` which given a sentence, returns 
-the top `EsaProcessor.RETURN_NUM` candidate Wikipedia concepts
-
-#### `ElmoProcessor`
-
-Supports all operations related to ElMo and its data files.
-
-A main entrance is `ElmoProcessor.rank_candidates`, which given a sentence and a list 
-of candidates (generated from ESA), rank them by ELMo representation cosine similarities. (see paper)
-
-It will return the top `ElmoProcessor.RANKED_RETURN_NUM` candidates.
-
-#### `InferenceProcessor`
-
-This is the core engine that does inference given outputs from the previous processors.
-
-The logic behind it is as described in the paper and is rather complicated. 
-
-One main entrance is `InferenceProcessor.inference` which receives a sentence, outputs from 
-previously mentioned processors, and set inference results.
-
-#### `Evaluator`
-
-This evaluates performances and print them, after given a list of sentences processed by
-`InferenceProcessor`
-
-#### `DataReader`
+It's generally an expensive operation to run on large numerb of new sentences, but you are welcome to do it.
+Please refer to `main.py` and [Engineering Details](https://github.com/CogComp/zoe/wiki/Engineering-Details) 
+to see how you can test on your own data. 
 
-Initialize this with a data file path. It reads standard json formats (see examples)
-and transform the data into a list of `Sentence`
 
 ## Citation
 See the following paper: