Natural Language Processing
Apply the merge the vocabulary learned
BOTIE
Examples, experiments and workspace controls
Connect a tool's inputs to see what it produces. You can try a branch before connecting it to Result.
Try your own inputs
Use a copy of the example to try your own data. Keep the problem's assumptions in mind, and predict the effect of a change before checking the output. You can also add another branch to compare two ways of doing the calculation.
Context for this challenge
Split into characters and apply the learned l-plus-o merge.
Storing every possible word is impractical, but frequent neighbouring pieces can be reused. The merge order has already been learned from a corpus. Let's apply those merges in order and see how they build the pieces for these words.
Inspect the component calculation
Merge an adjacent pair(
Pieces: Read Unicode code points(
Text: Word
)
Left piece: l
Right piece: o
)Examples and results
- Word
lower
- Required result
- 0lo
- 1w
- 2e
- 3r
Try a fresh construction
This clears this draft, including its undo history. Earlier successful attempts stay recorded. Build again without opening hints to record an independent attempt.
Stuck? Inspect a worked construction
The tools below form one possible solution. You can assemble it, follow its signals, and undo that change to return to your own construction.
Assumptions and test precision
This is a small construction problem. The lesson explains the assumptions and the parts of the full method that this example leaves out. Numerical tests allow a difference of 0.001. Lists and structures must also have the right shape.
Your last tested pieces can start the full construction. An existing draft there keeps its own pieces.
The learned merge appears inside another word
This check uses the pieces from “Replay the learned merges in their specified order”.
BOTIE
- Word
follow
Use a number, text, or an array matching the requested result. For a matrix, put each row in brackets. Saving your prediction runs your current construction on these inputs and checks the earlier examples too.
Build a construction in the workspace above first. This case will test those pieces.
Which part of BPE learning is absent when the merge rules are already supplied?
Replaying merges tokenizes text; learning their order requires corpus statistics.
This is a small construction problem. The lesson explains the assumptions and the parts of the full method that this example leaves out.
Work through the Python challenges →