Hyperspace Analogue to Language slides a ten-word window along the text. A word right next to the target counts 10, a word ten away counts 1. Watch the two matrices fill and notice they are not the same matrix.
Distance is information. A word sitting immediately to the left of woodchuck
tells you far more about it than a word nine positions away, so HAL ramps the weight from 10
down to 1 instead of counting every neighbour once.
The two matrices are the reason this lab exists. Filling from the left and filling from the right do not produce mirror images, because "chuck wood" and "wood chuck" are different facts about the language. HAL keeps both, which is why the full HAL vector for a word is its row and its column stuck together, twice as long as the vocabulary.
This animation uses the woodchuck sentence and a ten-word window, so it is a bigger run
than the one in the book: hal.py works a seven-word sentence with a window of five,
small enough to check every cell by hand.
Reference: Lund and Burgess, Producing high-dimensional semantic spaces from lexical co-occurrence, Behavior Research Methods, Instruments and Computers, 28(2):203, 1996.