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POStrategy for parsing natural language descriptions into structured data
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  1. POStrategy for parsing natural language descriptions into structured data
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    copied!<p>I have a set of requirements and I'm looking for the best <strong>Java-based</strong> strategy / algorthm / software to use. Basically, I want to take a set of recipe ingredients entered by real people in natural english and parse out the meta-data into a structured format (see requirements below to see what I'm trying to do).</p> <p>I've looked around here and other places, but have found nothing that gives a high-level advice on what direction follow. So, I'll put it to the smart people :-):</p> <p>What's the best / simplest way to solve this problem? Should I use a natural language parser, dsl, lucene/solr, or some other tool/technology? NLP seems like it may work, but it looks really complex. I'd rather not spend a whole lot of time doing a deep dive just to find out it can't do what I'm looking for or that there is a simpler solution.</p> <h1>Requirements</h1> <p>Given these recipe ingredient descriptions....</p> <ol> <li>"8 cups of mixed greens (about 5 ounces)"</li> <li>"Eight skinless chicken thighs (about 1¼ lbs)"</li> <li>"6.5 tablespoons extra-virgin olive oil"</li> <li>"approximately 6 oz. thinly sliced smoked salmon, cut into strips"</li> <li>"2 whole chickens (3 .5 pounds each)"</li> <li>"20 oz each frozen chopped spinach, thawed"</li> <li>".5 cup parmesan cheese, grated"</li> <li>"about .5 cup pecans, toasted and finely ground"</li> <li>".5 cup Dixie Diner Bread Crumb Mix, plain"</li> <li>"8 garlic cloves, minced (4 tsp)"</li> <li>"8 green onions, cut into 2 pieces"</li> </ol> <p>I want to turn it into this....</p> <pre> |-----|---------|-------------|-------------------------|--------|-----------|--------------------------------|-------------| | | Measure | | | weight | weight | | | | # | value | Measure | ingredient | value | measure | preparation | Brand Name | |-----|---------|-------------|-------------------------|--------|-----------|--------------------------------|-------------| | 1. | 8 | cups | mixed greens | 5 | ounces | - | - | | 2. | 8 | - | skinless chicken thigh | 1.5 | pounds | - | - | | 3. | 6.5 | tablespoons | extra-virgin olive oil | - | - | - | - | | 4. | 6 | ounces | smoked salmon | - | - | thinly sliced, cut into strips | - | | 5. | 2 | - | whole chicken | 3.5 | pounds | - | - | | 6. | 20 | ounces | forzen chopped spinach | - | | thawed | - | | 7. | .5 | cup | parmesean cheese | - | - | grated | - | | 8. | .5 | cup | pecans | - | - | toasted, finely ground | - | | 9. | .5 | cup | Bread Crumb Mix, plain | - | - | - | Dixie Diner | | 10. | 8 | - | garlic clove | 4 | teaspoons | minced | - | | 11. | 8 | - | green onions | - | - | cut into 2 pieces | - | |-----|---------|-------------|-------------------------|--------|-----------|--------------------------------|-------------| </pre> <p>Note the diversity of the descriptions. Some things are abbreviated, some are not. Some numbers are numbers, some are spelled out. </p> <p>I would love something that does a perfect parse/translation. But, would settle for something that does reasonably well to start.</p> <p>Bonus question: after suggesting a strategy / tool, how would you go about it?</p> <p>Thanks!</p> <p>Joe</p>
 

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