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Emily Pace is the Principal Linguist at Expert System USA. She earned her MS in Theoretical Linguistics from Georgetown University, where she also studied French and Arabic as an undergraduate. Guest blogger Anna Dausman had the pleasure of speaking with Emily, and their conversation covered a range of topics, from Emily’s path in linguistics, to her current work in the field of text analysis. Her story is a testament to the placement of a linguist with both soft skills and computational expertise.
What follows is Part I of the interview with Emily Pace – Knowledge Engineering & Text Analysis. Stay tuned for Part II next Wed
- Part I takes us into Emily’s work in text analysis and knowledge engineering.
- Part II follows Emily’s path in linguistics, her experience in graduate school, and why she advocates taking a break before returning to advanced graduate studies.
Anna: How would you define text analysis, in the context of knowledge management?
Emily: Ultimately, the focus of text analysis is to replicate the human ability and experience of processing text. Everyone wants a product that does what actual people can do when they read. Every agency looking at every kind of message stream wants to know, ‘If a person read this, what would they do with it? How would they interpret it? What information would stand out as interesting or important?’
Anna: Can you tell me more about Expert System USA, the company you work for?
Emily: Expert System USA (ESUSA) is an American subsidiary of a global semantic intelligence company. We’re a software company that provides products and services to clients with large volumes of mostly unstructured data that needs to be analyzed. We help people find the information in text that is relevant for their mission. The branch where I work solely partners with clients in US public sector. While the technology products at ESUSA have been in development for a long time, the day-to-day environment feels very much like a startup. For example, when I first started working here, there were officially two employees: my boss, and me. Over the last year and a half, we’ve continued to expand.
I started off at ESUSA as a knowledge engineer. My base duty in this capacity had to do with building customized text analysis solutions for our clients using our in-house development tools. In order to do this, I needed to have a strong understanding of our capabilities, as well as the ability to understand the client’s needs. Once we know what they want, we can build a custom project on top of our out-of-the-box NLP capabilities.
Since then, I’ve changed roles, and am now the Principal Linguist. In addition to supervising our team of knowledge engineers, I also do a lot of project management. Even though my daily workflow is very different now, the work is conceptually quite similar to the knowledge engineering task: it’s all about figuring out what the client really wants and then finding innovative ways to meet their needs.
Anna: What types of data does this software work with?
Emily: Well, generically, all types of documents that contain primarily unstructured data (mostly narrative of some type). Documents may contain some structured fields, as well. Our focus is really on helping clients triage the massive amount of data that all organizations are swimming in these days. After this, the next step differs depending on the client: maybe they want to pass certain types of documents off to a subject matter expert or analyst, maybe they want to use what we produce as data for modeling purposes, it really just depends on the client and their needs.
Anna: What are some of the skills you use on a daily basis?
Emily: When I take ownership of a project, I leverage the same skillset I used in graduate school when I was confronted with a new topic that I didn’t know a lot about. It means doing some research on your own, talking to people, and being unafraid to be direct and say, ‘I don’t really get this. Can you elaborate?’ For me, asking for help in a professional setting is just like raising your hand in class, or going to a professor’s office hours. And this is key, because if I don’t understand what the client wants, our developers will never understand that either.
Being a linguist helps you to be tuned into what people are really saying, especially when they’re expressing themselves vaguely. It helps when you’re doing research or reading documentation to be able to pinpoint these areas and say, ‘This isn’t quite clear; What do you mean by this?’ We have to make sure we understand both their needs and their wants, and they understand what we can do in the amount of time we have.
Anna: What skills are valued (cultivated) in the field of knowledge engineering and text analysis?
Emily: For me, a mix of technical skills and interpersonal skills is very important – even a basic knowledge of statistics and some programming skills (in my case Python). I was hired to help bridge the communication gap between the technical teams and clients who aren’t familiar with the jargon or the process.
You need someone who can talk to clients and walk them through the basics of the project without getting bogged down in the precise details of the technology, but who also understands the technology well enough to implement the client’s vision. When I talked to my graduate school advisor about looking for jobs outside of academia, he put it simply: “I think the role for you is to be the one talking to both the nerds and the regular people.” This is basically what I do now.
This interview has been edited and condensed.
Guest Blogger Anna Dausman is a linguist and storyteller based in Philadelphia, Pennsylvania. Anna earned her BA in English and Linguistics from the College of William & Mary, and is pursuing an MS in Public Administration from Fels Institute of Government. You can reach Anna at firstname.lastname@example.org.