It's like trying to find typos in your own writing. It's very difficult to stay focused when reading a long series of nearly identical documents. The people you're talking about are reading a lot of novel documents.
Why would these be identical? New stories everyday, new games played etc.
If the only data you have about a game is the sport, the team names, and the score, there's only so much an AI (or a human!) can do to write an interesting article about it. Once you've read a few dozen of the generated articles, they'll all start sounding the same -- because, aside from the details, they are all the same.
If you want quality articles, you need some more depth in the source data. And, for little-league sports games, that data may just not exist.
One article even failed to populate properly, with the text instead featuring a bracketed glimpse at how its opening sentence was supposed to read.
"The Worthington Christian [[WINNING_TEAM_MASCOT]] defeated the Westerville North [[LOSING_TEAM_MASCOT]] 2-1 in an Ohio boys soccer game on Saturday," reads the butchered intro.
Comments
It's like trying to find typos in your own writing. It's very difficult to stay focused when reading a long series of nearly identical documents. The people you're talking about are reading a lot of novel documents.
Why would these be identical? New stories everyday, new games played etc.
If the only data you have about a game is the sport, the team names, and the score, there's only so much an AI (or a human!) can do to write an interesting article about it. Once you've read a few dozen of the generated articles, they'll all start sounding the same -- because, aside from the details, they are all the same.
If you want quality articles, you need some more depth in the source data. And, for little-league sports games, that data may just not exist.
Because they're populating a template.