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This is code developed by BBN to support the 2016 TAC KBP Event Argument and Linking Shared Task. A description of this task will be released soon.

This repository contains three artifacts:

  • tac-kbp-eal contains classes to represent system responses and assessments for the task. While these are mainly to support the executables in this repository, if your system is based on Java or another JVM language, you are strongly encouraged to use them. Note that they can be used from Python via Jython.
  • tac-kbp-eal-scorer contains the scoring code.
  • bin contains all the non-java executables

Building

Requirements:

Build steps:

  1. grep "<bueopen.version>" pom.xml and note the version given (e.g. 4.10.0). We'll call this X.
  2. checkout https://github.com/BBN-E/bue-common-open . From there,
  3. git fetch --tags
  4. git checkout common-all-open-X
  5. mvn install
  6. you can now return to this repository and mvn install

The first two steps need only be repeated when the version of bue-common-open depended on changes.

If you are building from an IDE, you will need to set up annotation processors

Quick Start

If you just want to use this to recreate the 2016 evaluation scoring (or 2017 when the evaluation references are released) see the evaluation documentation.

Using

The event argument linking is a complex task with a necessarily complex scoring process. We will present a brief overview here, but the task description is the authoritative description.

Systems submitted to the evaluation will produce three outputs given a corpus:

  • for each document, the set of document-level event arguments. For example, a system may say "Bob is the Agent of a Movement.Transport-Artifact event in document foo123 with realis Other and this claim is justified by the following text 'lorem ipsum....'"". We call claims like the preceding sentence system responses (Java class Response). The collection of system responses given by a system for a document is an ArgumentOutput. In document-level scoring we will also talk about TRFRs (for type-role-filler-realis; Java TypeRoleFillerRealis). A TRFR is an assertion like "Bob is the Agent of a Movement.Transport-Artifact event in document foo123 with realis Other" independent of any text justifying this claim. So a system could potentially output multiple justifying responses for each TRFR; for example, it could find one mention of the above event using the string Bob Smith as the participant and another mention in another sentence with Mr. Robert Smith. These would be two responses which correspond to a single TRFR.
  • for each document, an event linking. This groups all the document-level event arguments which are part of the same event. The groups are called event frames or event hoppers. There are two two ways of looking at event frames and therefore two ways of representing them in the code. You can look at them at the level of Responses, in which case you have ResponseSets grouped into a ResponseLinking, or you can think of them in terms of TRFRs, in which case you have TypeRoleFillerRealisSets grouped into an EventArgumentLinking. An event frame can be referred to by its document ID and event frame ID together, yielding a DocEventFrameReference.
  • over the whole corpus, a grouping of document-level event frames which correspond to the same event. Each group of event frames is a CorpusEventFrame made up of DocEventFrameReferences. All the CorpusEventFrames for a corpus together make a CorpusLinking.

A ArgumentOutput and a ResponseLinking for a single document can be joined to make a DocumentSystemOutput2015. The collection of all DocumentSystemOutput2015s and the CorpusLinking together form a SystemOutputStore2016.

Scoring is done in two ways:

  • document-level arguments and event frames are scored against document annotations in ERE format.
  • corpus-level event frames are scored by query and assessment.

Scoring document-level event arguments

The program ScoreKBPAgainstERE can take a SystemOutputStore2016 and documents in the LDC's ERE format and produce a document-level scores. ScoreKBPAgainstERE offers several methods for aligning an EREEntitytMention or EREFiller to a system Response (referred to as Arguments, rules in decreasing priority):

  • By exact match for CAS (Canonical Argument String) offsets to Argument or the Argument head
  • By exact match for Argument head and the head of the CAS offsets (see [Using CoreNLP](# using-corenlp) for details)
  • By either the CAS containing the Argument or visa versa, and heads being included in both of them. (see [Using CoreNLP](# using-corenlp) for details)

In the code you will occasionally see references to scoring document-level event arguments by assessment. This was done in 2014 and 2015 and the code has been kept for backwards compatibility.

The heads are not necessary to run scoring, but will give a better alignment to the gold standard. It is recommended that any development system use the head scoring as it is what is run in the official evaluation. See [Using-CoreNLP](section regarding using CoreNLP).

Using CoreNLP

The use of CoreNLP processed documents for scoring-relaxation purposes is optional.

The ScoreKBPAgainstERE program provides several options for scoring more relaxed than exact match. Among those options is using CoreNLP version 3.6.0 to parse and Collins-Style head rules to find the head node corresponding to the base filler. This "discovered head" and its offsets are then:

  • used for exact match to find an Argument head
  • used to find an Argument that contains the discovered head.

See EnglishAndChineseHeadRules under BBN's common core code open source releases for English and Chinese citations.

These relaxations are produced by running the CoreNLP pipeline with options documented in CoreNLPXMLLoader (prefer that as canonical source). For convenience, the last used options are: -annotators tokenize,cleanxml,ssplit,parse -tokenize.options invertible -outputFormat xml. This output is fed into the scoring pipeline in a file with newline separated file of "docid\t/path/to/corenlp/doc".

Scoring document-level event hoppers

Coming soon.

Scoring corpus-level event frames

The LDC will prepare a collection of queries for the corpus-level evaluation. Each query will identify a unique event in the document. CorpusQueryExecutor2016 will match each query against a system's output to see what documents the system believes contain references to the indicated event. Each of these matches are then sent to LDC annotators for assessment, producing a CorpusQueryAssessments object.

At scoring time CorpusScorer repeats the query matching process, but this time the resulting matches are compared against LDC assessments and a score is produced.

Evaluation Workflow

The following workflow will be used during the evaluation. All executables referenced below may be found in either tac-kbp-eal/target/appassembler/bin or tac-kbp-eal-scorer/target/appassembler/bin.

  • a 'quote filter' to remove material with CAS and BF offsets in quoted regions will be built from the original text of the data set.
  • competitor submissions will be validated using validateSystemOutput2016.
  • all material from quoted regions will be removed from competitor submissions.
  • document-level scores will be created using ScoreAgainstERE on competitor submissions and LDC ERE annotations.
  • the corpus-level queries will be run against all systems. The LDC will assess the resulting matches.
  • CorpusScorer will be run against the competitor submissions and the resulting LDC assessments.

Parameter Files

Most of the executables take parameter files as input. These have the format

key1: value1
# this is a comment!
key2: value2
# include the params from this file
INCLUDE file.params
# use the value of key2
key3: %key2%/value3
# override a previous defined param
OVERRIDE key4: value4

validateSystemOutput2016

This program will check that your submission:

  • has the correct format
  • contains only legal event roles and types

If either of these fail, the program will halt with an error message. In the future, we plan to add enforcement of rules concerning what portions of answers may come from within <quote> regions.

Additionally, this program will dump to standard output a human-readable version of your responses with all offsets resolved to strings from the original documents so that you can check for mistakes.

This program takes the following parameters:

  • systemOutputStore: the path of the system output store to be validated
  • validRoles: is data/2016.types.txt (for KBP 2016)
  • linkableTypes : is data/2016.linkable.txt (for KBP 2016) - for each event argument type, valid argument types for it to be linked to.
  • dump: whether to dump response to stdout in a human readable format.
  • docIDMap: (required if dump is true) a list of tab-separated pairs of doc ID and path to the them to standard output.

NISTValidator2016

This program performs the same operations as validateSystemOutput2016 but with the frontend used by NIST in their evaluation website.

Its usage is NISTValidator2016 rolesFile linkableTypesFile docIdToOriginalTextMap [VERBOSE|COMPACT] submissionFile where:

  • roleFiles is data/2016.types.txt
  • linkableTypesFile is data/2016.linkable.txt
  • docIdToOriginalTextMap is a file, one entry per line, with docid tab /path/to/raw/ldc/file
  • [VERBOSE|COMPACT] the level of detail in error messages
  • submissionFile is the file you provide to NIST

ScoreAgainstERE

Scores system output against an annotation store.

CorpusScorer

The program takes the following parameters:

  • com.bbn.tac.eal.outputDir: directory to output scoring information to
  • com.bbn.tac.eal.queryFile: file describing queries to execute
  • com.bbn.tac.eal.queryAssessmentsFile: file containing LDC assessments of query matches
  • com.bbn.tac.eal.systemOutputDir: system output to score

Baseline linking

We provide a baseline implementation of event argument linking for those who wish to try out the scorer but have not yet developed their own algorithm. This baseline implementation simply links together all arguments of the same event type in a document. To run this, use ApplyLinkingStrategy.

Parameters:

  • argumentSystemStore: the system's argument output
  • linkingSystemStore: the path to write the baseline linking to

Questions

How can I use the Response, etc. in my system's code?

Add the following to the dependencies section of your project's pom.xml (or take similar steps if using Gradle, etc.):

<dependency>
      <groupId>com.bbn.kbp.eal</groupId>
      <artifactId>tac-kbp-eal</artifactId>
      <version>current version listed in pom.xml of this repository</version>
</dependency>

This artifact is not deployed to Maven Central, so you will need to install it in your local repository as described above.

Contact

For questions concerning the software, please contact [email protected]. If you have bugs or feature requests, you can use the GitHub Issue Tracker. The issue tracker is preferred so future users can benefit from the answers to your questions. To track changes to this repository, follow https://github.com/BBN-E/tac-kbp-eal/commits/master.atom in an RSS reader.

Export Control Marking

Distribution Statement "A" (Approved for Public Release, Distribution Unlimited)

WARNING - This document contains technology whose export or disclosure to Non-U.S. persons, wherever located, is subject to the Export Administrations Regulations (EAR) (15 C.F.R. Sections 730-774). Violations are subject to severe criminal penalties.