Natural Language Processing Applied to Archival Description of Textual E-records

Natural Language ProcessingN t lL P i Applied to Archival Description of Textual E-records E- William Underwood Georgia Tech Research Institute Atlanta, Georgia WVU/NETL/ERA Workshop on Digital Preservation of Complex Engineering Data WVU NRCCE, Morgantown, West Virginia April 20-21, 2009

Archival Description Method for extracting metadata from g textual e-records Use of the metadata in archival description Next StepsOverview

Archival Description includes: ◦ The titling of records that do not have titles ◦ The summary of the content of records, folders of records and series of records. ◦ When time allows, the creation of other finding allows aids such as subject indexes to record series.Archival Description

Archivists cannot describe a series until the record series has been manually read and reviewed. ◦ With increasing volumes of e-records, it may be decades, even centuries, before new acquisitions are described. In I responding to FOIA requests, A hi i t need to be able di t t Archivists dt b bl to search collections of e-records with high precision and recall. ◦ However at the time of responding to FOIA requests archivists However, requests, have not read all of the records, so cannot index the records and search on document types, dates of records, author’s and addressee’s names and the topics of records. ◦ The results set of a query is a list of file names, not record titles and summaries of contentArchival Description:Research Motivation

Descriptions of records include names of s p o so o ds ud a so author(s) and addressees, topics, actions and sometimes dates.Example of an item (record) description from NARA’s Archival Research Catalog (ARC) This letter was typewritten by President George H. W. Bush and addressed to his children: George, Jeb, Neil, Marvin, and Doro. He expresses his happiness at their Christmas celebration held at Camp David then writes concerning his David, conflicted feelings as he prepares for the possibility of war with Iraq.Archival Description:Item Scope and Content Note

Input: Textual Document1. Information Extraction2. Document Type Recognition3.3 Speech Act Transducer4. Discourse Analysis for Topic RecognitionOutput: [document(e1), author(e1, S), addressee(e1, H), act(e1 F(P)), topic(e1, T), date(e1, D)]A Method for Extracting Metadata forArchival Description

Information extraction (semantic tagging) o a o a o (s a agg g) is a technology used to identify and annotate semantic categories in text (e.g. names of persons, organizations and locations, job titles, dates). 1. Document Reader 2. English Tokenizer 3. Wordlist Lookup + enhanced wordlists 4. Sentence Splitter 5. Hepple POS Tagger + lexicon pp gg 6. Semantic Tagger + Named Entity RulesInformation Extraction: Method

Person_female_first.lst (8263) ( ) Person_female_first_ambig.lst (117) Person_male_first.lst (3704) Person_male_first_ambig.lst (1 117) P l fi t bi l t (1,117) Person_surname.lst (83,805) Person_surname_ambig.lst Person surname ambig.lst (6,802) Person_headofstate_90.lst (478) Location_city_US.lst (33,017) Location_city_us_ambig.lst (5,478) Location_foreign_city.lst (3802)Information Extraction:Wordlist Lookup

Java Annotation Pattern Engine(JAPE) Rules

Annotated Person Namesand Job Titles

Information Extraction:Performance

Agenda NewsletterBar Chart Nomination to Federal OfficeBiography NotesBriefing Memo Presidential StatementDecision Memo Press Pool ReportCorrespondence Press ReleaseDiary Referral MemoExecutive Order ResumeInformation Memo ScheduleJob Application Signature MemoList of Candidates for Federal Situation Report Office SummaryMailing List Transcript of SpeechMemo Telephone CallMinutes of Meeting RecommendationNational Security Directive Transcript of News Conference (NSD)Document Types

Input: Annotated text from Information pu oa d o o a o Extractor1. Intellectual Element Annotator + Intellectual Element Rules2. SUPPLE Parser/Interpreter + Document Type G T Grammars augmented with t d ith Semantics3 Extract Metadata3.Output: [document(e1), author(e1, S), addressee(e1, H), topic(e1, T), date(e1, D)]Document Type Recognition

Document Types:Intellectual Element Recognition

Document Types: Grammar for theStructure of a Memorandum

Document Types: Grammar forMemorndum with Semantic Rules

Parse Tree and Semanticsof a Document

Document_Type = memo A memorandum dated AprilDate = April 27, 1992 27, 1992 from EDEAuthor = SAM SKINNER Holiday to Sam SkinnerAddressee = EDE HOLIDAY regarding California Earthquake.Topic = California p EarthquakeExtracted Metadata andItem Description

1. Annotation of Explicit Speech Acts 2. Annotation of Implicit S 2 A i fI li i Speech Acts hA 3. Annotation of Speech Acts Indicated by Text Structure 4. Annotation of Indirect S 4 A t ti f I di t Speech Acts hA t 5. Annotation of the Primary Speech ActsSpeech Act Transducer

Performative verb - Verb whose action is accomplished merely by saying it or writing it. I recommend that you attend the conference. Illocutionary force of a message. recommend Propositional content of a message you attend the conference An explicit performative sentence is a sentence in which the illocutionary force is made explicit by naming the force. I promise to be there An implicit performative sentence is a sentence in which the illocutionary force is not made explicit by naming the force. f I shall be thereSpeech Acts

Declarative, imperative and interrogative a a , p a a d oga sentences also express speech acts. Declarative (state) ◦ You completed the report. Imperative (request) ◦ Pl Please, complete the report. l t th t Interrogative (ask) ◦ Did you complete the report?Speech Acts: Implicit

An indirect speech act is a speech act that p p is performed indirectly by way of performing another. Can you pass the salt? (ask) in the appropriate context means Please, pass the salt. (request) Textual structure can also indicate illocutionary force. Example: a section heading RECOMMENDATIONS can indicate the sentences in a section have the illocutionary force recommend.Speech Acts

assert, deny, state, declare(1), tell(1), report, advise(1), remind, info m certify(1), agree(1), acknowledge, emind inform, ce tif (1) ag ee(1) ackno ledge praise(1), commit, pledge, direct, request, ask(1), ask(2), urge, encourage, invite, order(1), prohibit, suggest(2), p p propose, recommend, declare(2), resign, confirm, , , ( ), g , , nominate, appoint, authorize, pray, terminate, veto, approve(1), disapprove, revoke, mourn, congratulate, thank, apologize, and welcome(2). concur, salute, amend, counsel, welcome(1), tender(2), call on, block, retire, proclaim, delegate, designate, determine, find, reject(2), endorse, appreciate, regret, trust(1) , believe, want, desire, and intend.Speech Acts in PresidentialRecords

Signature Memorandum from Boyden Gray to the President recommending the nomination of Ronald B. Leighton to be a US District Judge. Letter from President Bush to President Mikhail Gorbachev suggesting an informal meeting. Memorandum from President Bush to Boyden Gray requesting an a a ys s o t e a o e s eso ut o analysis of the War Powers Resolution. Letter from Susan Black to President Bush expressing appreciation for nomination and commitment to serve. Referral Memorandum from Sally Kelley to FEMA requesting appropriate action to a letter from Beryl Anthony to the President.Uses of Extracted Metadatain Automatic Description

Inducing grammars for documentary form from samples Create rules for annotating implicit speech acts and speech acts indicated by textual structure. p y Evaluate performance of Speech act recognition method Recognition of the topics of sentences Discourse Analysis to identify primary topic(s) of records Generate item, folder and series descriptions and item evaluate the methodNext Steps

Website: perpos.gtri.gatech.edu p p g gW. Underwood and S. Isbell, Semantic Annotation of Presidential E Records Technical Report E-Records, ITTL/CSITD 08-01, May 2008W. Underwood and S. Laib. Automatic Recognition of Documentary Forms, Technical Report ITTL/CSITD 08-02, May 2008W. UnderwoodW Underwood. Recognizing Communication Acts in Presidential E-Records. Technical Report ITTL/CSITD 08-03, October 2008Additional Information

Natural Language Processing Applied to Archival Description of Textual E-records

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