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Content Engineering

Reading, Writing, and Entities

Reading involves work and writing is difficult.  Countless books are available on how to write.  What could be left to say?  In view of all the writing advice that’s available, it’s surprising that one topic gets scant coverage: entities.  Not many writers talk about their use of entities in their writing.  I believe entities can be powerful lens for considering writing and the reader experience.

What’s an entity?  It is not a word used much in colloquial speech.  But it’s a handy term to refer to nouns that have a specific identity.  Merriam-Webster lists some synonyms of entity: “being, commodity, individual,  object, substance, thing.”  These words used to suggest the idea of an entity may seem vague, but specific examples of entities can be concrete. Most commonly people associate entities with organizational units, such as a corporate entity.  But the term can refer to all kinds of things: people, places, materials, concepts, brands, time periods, or space aliens.   Merriam-Webster cites the following usage example: “the question of whether extrasensory perception will ever be a scientifically recognized entity.”  In this example, the term entity refers to a phenomenon that many people don’t consider real: ESP.  The characters in Harry Potter novels can be entities, as can a celebrity or a football team.  

Perhaps the easiest way to think about an entity is to ask if something would have an entry in the encyclopedia — if so, it is likely an entity.  Entities are nouns referring to a type of thing  (a category, such as mountains), or a specific individual example of a thing (a proper noun, such as the Alps).  Not all nouns are entities: they need to specific and not generic.  A window would probably be too generic to be an entity — without further information, the reader won’t think too much about it.  A double glazed window, or a window on the Empire State Building, would be an entity, because there’s enough context to differentiate it from generic examples.  Windows as a category could be an entity, since they can be considered in terms of their global properties and variations: frosted windows, stain-glass windows, etc.  While there is no hard and fast rule about what’s considered an entity, the more salient something is in the text, the more likely it is be an entity.  A single mention of a generic window would not be an entity, but a longer discussion of windows as an architectural feature would be.

Entities are interesting in writing because they carry semantic meaning (as opposed to other kinds of meaning such as mood or credibility.)  Entities in writing make writing less generic.  They overlap with the concept of detail in writing.  But the role that entities play is different from making writing vivid by providing detail.  Entities are the foreground of the writing, not the background.  Many details in writing such as the brand of scarf that a protagonist wears are not terribly important.  Details are background color and in some writing are extraneous.  Entities, in contrast, are the key factual details mentioned in the text.  They can be central the content’s meaning.

Ease of reading and understanding

Clarity is an obsession of many writers.  Entities can play an important role in clarity.

I became more mindful of the role of entities in writing while reading a recent book of jazz criticism by Nate Chinen.  I enjoy learning about jazz, and the writer is very knowledgeable on the subject. He personally knows many of the people he writes about, and can draw numerous connections between artists and their works.  Yet the book was difficult to read.  I realized that the book talked about too many entities, too quickly.  A single sentence could mention artists, works, dates, places, music style, and awards.  While I know a bit about jazz, my mind was often overloaded with details, some of which I didn’t understand completely.  I felt the author was at times was “name checking” by dropping names of people and things he knew and that the reader should be impressed he knew.

Chinen created what I’ll call “dense content” — text that’s full of entities.  His writing provides a negative example of dense writing.  But not all dense content is necessarily hard to understand.

If dense content can be difficult to understand, is light content a better option?  Should entities be mentioned sparingly?

Light content is favored by champions of readability.  Writing should be simple and easy to read, and readability advocates have devised formulas to measure how readable a text is.  Texts are scored according to different criteria that are believed to influence readability:

  1. Sentence length
  2. Syllables per sentence.
  3. Ratio of commonly used words as a portion of the entire text.

All these metrics favor the use of short, simple words, and tend to penalize extensive reference to entities, which can be unfamiliar and longer words.

So if readability scores are maximized, does understanding improve?  Not necessarily.  Highly readable content, at least as scored according to these metrics, may in fact be vague content that’s full of generalities and lacking concrete examples.  The concept of readability confuses syntactical issues (the formation of sentences) with semantic ones (the meaning of sentences).  Ease of reading is only partly correlated with depth of understanding.

The empty mind versus the knowing  mind

One of the limitations of readability as an approach is that it doesn’t consider the reader’s prior knowledge of a topic.  It assumes the reader has an empty mind about the topic, and so nothing should be in doubt as to meaning.  Readability incorporates a generic idea of education level, but it is silent about what different people know already.  For example, my annoyance at the jazz criticism book may a sign that I wasn’t the target audience for the book: I over-estimated my knowledge, and have blamed the author for making me feel unknowledgeable.  Indeed, some readers are enthusiastic about the dense detail in the book.  I, however, wanted more background about these details if they were considered important to mention.  

One way to extend the concept of readability to incorporate understanding is to measure the use of entities in writing.  I would suggest two concepts:

  1. Entity density
  2. Entity novelty

Entity density refers to how many different entities are mentioned in the text.  Some text will be more dense with entities compared with other text.  Entity density could measure entities per sentence, or total entities mentioned in an article.  Computers can already recognize entities in text, so an application could easily calculate the number of entities in the article, and the average per sentence.  

Example of computer recognition of entities in text.

 

Entity novelty takes the idea a step further.  It asks: how many new entities are introduced in the text for the reader?  For example, I’ve been discussing an entity called “readability.”  I am assuming the reader has an idea what I am referring to.  If not, readability would be a novel entity for the reader.  It is more difficult to calculate the number of unknown entities within a text.  Perhaps reading apps could track if the entity has been frequently encountered previously.  If it was, then it could assume it was no longer novel.

The idea behind these metrics is to highlight how entities can be either helpful or distracting.  The text could have many entities and be helpful to the reader, if the reader was already familiar with the entities.  The text can include unfamiliar entities, provided there aren’t too many.  But if the text has too many entities that are novel for the reader, both readability and understanding may suffer.

Scanning and entities

Another dimension that readability metrics miss is the scan-ability of text.  The assumption of readability is that the entire text will be read.  In practice, many readers choose what parts of the text to read based on interests and relevance.  The mention of entities in text can influence how easily readers can find text of interest.  Readers may be looking for indications that the text contains material that they:

  • Already know
  • Are not interested in
  • Know they are interested in
  • Find unfamiliar but are curious about.

Instead of considering text from the perspective of the “empty mind,” scan-ability considers text from the perspective the “knowing mind.”  Readers often search for concrete words in text, especially capitalized proper nouns.  Vague, generic text is hard to scan.  

Imagine a reader who wants to know about Japan’s banking system.  What entity would they look for?  That will depend partly on their existing knowledge.  If they want to know who is in charge of banking in Japan, they will look for mentions of specific entities.  Perhaps they know the name of the person and will search for that name.  Or they may not know the name of the person, but have an idea of their formal title so they will look for a mention of the words “Japan,” “Bank,” and “Governor.”    If they don’t know the formal title, they might look for mentions of a person’s role, such as “head of the central bank.”  In text, all these entities (name, title, and role) could appear in a paragraph on the topic.   All aid in the scanning of text.

Entities can help readers find information another way as well.  Entities can be described with metadata, which makes the information much easier to find online when searching and browsing.  When computers describe entities, they can keep track of different terms used to describe them, so that readers can find what they need whether or not they know about the topic already.  Metadata can connect different aspects of an entity, so that people can search for a name, a title, or a role and be taken to the same information.

— Michael Andrews