Information Extraction from Single and Multiple Sentences

Information Extraction from Single and Multiple Sentences Mark Stevenson Department of Computer Science Regent Court, 211 Portobello Street, University of Sheffield Sheffield S1 4DP, UK marks@dcs.shef.ac.uk Abstract Some Information Extraction (IE) systems are limited to extracting events expressed in a single sentence. It is not clear what ef- fect this has on the difficulty of the extrac- tion task. This paper addresses the prob- lem by comparing a corpus which has been annotated using two separate schemes: one which lists all events described in the text and another listing only those expressed within a single sentence. It was found that only 40.6% of the events in the first anno- tation scheme were fully contained in the second. 1 Introduction Information Extraction (IE) is the process of identifying specific pieces of information in text, for example, the movements of company execu- tives or the victims of terrorist attacks. IE is a complex task and a the description of an event may be spread across several sentences or para- graphs of a text. For example, Figure 1 shows two sentences from a text describing manage- ment succession events (i.e. changes in corpo- rate executive management personnel). It can be seen that the fact that the executives are leaving and the name of the organisation are listed in the first sentence. However, the names of the executives and their posts are listed in the second sentence although it does not mention the fact that the executives are leaving these posts. The succession events can only be fully understood from a combination of the informa- tion contained in both sentences. Combining the required information across sentences is not a simple task since it is neces- sary to identify phrases which refer to the same entities, “two top executives” and “the execu- tives” in the above example. Additional diffi- culties occur because the same entity may be referred to by a different linguistic unit. For ex- ample, “International Business Machines Ltd.” may be referred to by an abbreviation (“IBM”), Pace American Group Inc. said it notified two top executives it intends to dismiss them because an internal investigation found ev- idence of “self-dealing” and “undisclosed fi- nancial relationships.” The executives are Don H. Pace, cofounder, president and chief executive officer; and Greg S. Kaplan, senior vice president and chief financial officer. Figure 1: Event descriptions spread across two sentences nickname (“Big Blue”) or anaphoric expression such as “it” or “the company”. These complica- tions make it difficult to identify the correspon- dences between different portions of the text de- scribing an event. Traditionally IE systems have consisted of several components with some being responsi- ble for carrying out the analysis of individual sentences and other modules which combine the events they discover. These systems were of- ten designed for a specific extraction task and could only be modified by experts. In an ef- fort to overcome this brittleness machine learn- ing methods have been applied to port sys- tems to new domains and extraction tasks …

Content truncated to 500 words