Fig. 10.1.14 shows how raw text is read and processed into a recognizable list in textual
ETL.

Fig. 10.1.14 List processing.

Consider the raw text:

“Recipe ingredients:

1—Rice

2—Salt

3—Paprika

4—Onions

.....................”

Textual could read the list and process it thusly:

Document name, byte, context—list recipe element 1, value—rice

Document name, byte, context—list recipe element 2, value—salt

Document name, byte, context—list recipe element 3, value—paprika

Associative Word Processing

Occasionally, there are documents that are repetitive in structure but not in terms of
words or content. In cases like these, it may be necessary to use a feature of textual ETL
called associative word processing.

In associative word processing, an elaborate definitional structure of data is created; then,
the words inside the structure are defined according to a common meaning of words.

Fig. 10.1.15 depicts associative word processing.

Chapter 10.1: Nonrepetitive Data