com.cobber.fta.plugins.LastName Maven / Gradle / Ivy
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Analyze Text data to determine simple type and Semantic type information as well as other key metrics associated with a text stream.
/*
* Copyright 2017-2024 Tim Segall
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.cobber.fta.plugins;
import java.util.Arrays;
import java.util.HashSet;
import java.util.Set;
import com.cobber.fta.AnalysisConfig;
import com.cobber.fta.AnalyzerContext;
import com.cobber.fta.Content;
import com.cobber.fta.Facts;
import com.cobber.fta.FiniteMap;
import com.cobber.fta.PluginAnalysis;
import com.cobber.fta.PluginDefinition;
import com.cobber.fta.SingletonSet;
import com.cobber.fta.core.FTAPluginException;
import com.cobber.fta.core.Utils;
import com.cobber.fta.token.TokenStreams;
/**
* Plugin to detect an individuals Last Name.
*/
public class LastName extends PersonName {
// This set covers the first two letters of ~95% of our last name list - assume this is a reasonable proxy for last names more generally
private final static String plausibleStarters[] = {
"AB", "AC", "AD", "AG", "AL", "AM", "AN", "AP", "AR", "AS", "AT", "AU", "AV", "AY",
"BA", "BE", "BI", "BL", "BO", "BR", "BU", "BY",
"CA", "CE", "CH", "CL", "CO", "CR", "CU",
"DA", "DE", "DI", "DO", "DR", "DU",
"EA", "EB", "EC", "ED", "EI", "EL", "EM", "EN", "ER", "ES", "EV",
"FA", "FE", "FI", "FL", "FO", "FR", "FU",
"GA", "GE", "GI", "GL", "GO", "GR", "GU",
"HA", "HE", "HI", "HO", "HU",
"IN", "IS",
"JA", "JE", "JO", "JU",
"KA", "KE", "KI", "KL", "KN", "KO", "KR", "KU",
"LA", "LE", "LI", "LO", "LU", "LY",
"MA", "MC", "ME", "MI", "MO", "MU",
"NA", "NE", "NI", "NO", "NU",
"OL", "OR", "OS", "PA",
"PE", "PH", "PI", "PL", "PO", "PR", "PU",
"QU",
"RA", "RE", "RH", "RI", "RO", "RU",
"SA", "SC", "SE", "SH", "SI", "SL", "SM", "SN", "SO", "SP", "ST", "SU", "SW",
"TA", "TE", "TH", "TI", "TO", "TR", "TU",
"UR",
"VA", "VE", "VI", "VO",
"WA", "WE", "WH", "WI", "WO", "WY",
"YA", "YO", "ZA",
"ZE",
};
private final static String badFirstWords[] = {
"NORTH", "SOUTH", "EAST", "WEST", "NEW", "OLD", "MOUNT", "LAKE"
};
private final static String badSecondWords[] = {
"HILL", "HILLS", "PARK", "SPRING", "SPRINGS", "RIDGE", "PARK", "VALLEY", "LAKE", "CREEK"
};
private final Set plausibleSet;
private final Set badFirstSet;
private final Set badSecondSet;
private String language;
private final static Set suffixes = new SingletonSet(new Content("resource", "/reference/en_name_suffix.csv")).getMembers();
private long lengthSum;
private long sampleCount;
private long bad;
/**
* Construct a Last Name plugin based on the Plugin Definition.
* @param plugin The definition of this plugin.
*/
public LastName(final PluginDefinition plugin) {
super(plugin, "lastnames.txt");
plausibleSet = new HashSet<>(Arrays.asList(plausibleStarters));
badFirstSet = new HashSet<>(Arrays.asList(badFirstWords));
badSecondSet = new HashSet<>(Arrays.asList(badSecondWords));
}
@Override
public boolean initialize(final AnalysisConfig analysisConfig) throws FTAPluginException {
super.initialize(analysisConfig);
language = locale.getLanguage();
return true;
}
@Override
protected boolean isPlausible(final String candidate) {
if (candidate.length() <= 2 || !plausibleSet.contains(candidate.substring(0, 2)))
return false;
// Assume 50% of the remaining are good - hopefully this will not bias the determination excessively.
// Use hashCode as opposed to random() to ensure that a given data set gives the same results from one run to another.
return candidate.hashCode() % 10 < 5;
}
/*
* Note: The input String will be both trimmed and converted to upper Case
* @see com.cobber.fta.LogicalType#isValid(java.lang.String)
*/
@Override
public boolean isValid(final String input, final boolean detectMode, final long count) {
final int ret = isValidCore(input, detectMode, count);
if (detectMode && count != 0) {
if (ret >= 1) {
sampleCount += count;
lengthSum += ret * count;
}
else if (ret == -1)
bad += count;
}
return ret > 0;
}
private boolean hasValidSuffix(final String input) {
final String trimmed = input.trim();
for (final String suffix : suffixes)
if (trimmed.endsWith(suffix))
return true;
return false;
}
private boolean averageLengthOK() {
if ("es".equals(language))
return (double)lengthSum/sampleCount < 2.5;
return (double)lengthSum/sampleCount < 1.5;
}
/*
* Handle the following cases:
* - Simple name, e.g. JEFFERSON
* - Space separate last names (max 3), e.g. BARON COHEN, DE LA RENTA
* - Hyphen separated name (max 2), e.g. DAY-LEWIS
* - Name followed by suffix, e.g. BUSH SR (or BUSH, SR)
*
* Return value:
* -1 = rubbish
* 0 = looks OK but does not pass validity test
* >1 = Number of words in a valid name
*/
private int isValidCore(final String input, final boolean detectMode, final long count) {
final String trimmedUpper = input.trim().toUpperCase(locale);
final int len = trimmedUpper.length();
int separatorOffset = -1;
char separator = ' ';
int spaces = 0;
for (int i = 0; i < len; i++) {
final char ch = trimmedUpper.charAt(i);
if (Character.isLetter(ch))
continue;
if (separatorOffset == -1 && (ch == '-' || ch == ' ' || ch == ',')) {
separatorOffset = i;
separator = ch;
continue;
}
if (separatorOffset != -1 && ch == '.')
continue;
if (ch != ' ')
return -1;
spaces++;
}
if (separatorOffset == -1)
return super.isValid(input, detectMode, count) ? 1 : 0;
if (separatorOffset < 2 || separatorOffset >= trimmedUpper.length() - 2)
return -1;
final String first = trimmedUpper.substring(0, separatorOffset);
if (!Utils.isAlphas(first))
return 0;
int wordCount = 2;
String second = trimmedUpper.substring(separatorOffset + 1).trim();
if (separator == ' ' && spaces != 0) {
final String[] words = second.split(" ");
second = words[0];
wordCount = words.length + 1;
if (wordCount > 3)
return -1;
}
if (separator == ',')
return hasValidSuffix(second) ? 1 : -1;
final boolean firstMatch = getMembers().contains(first);
// Reject a set of unlikely names (typically these are Cities)
if (separator == ' ') {
if (badFirstSet.contains(first) || badSecondSet.contains(second))
return 0;
if (firstMatch && hasValidSuffix(second))
return 1;
}
if (!Utils.isAlphas(second))
return 0;
final boolean secondMatch = getMembers().contains(second);
// Declares success if
// - both components of last name are good
// - either component of the hyphenated name is good
// - second component of the space separated name is good
if ((firstMatch && secondMatch) || ((firstMatch || secondMatch) && (separator == '-' || "es".equals(language))) || (secondMatch && separator == ' '))
return wordCount;
if (!detectMode)
return wordCount;
return separator == '-' && isPlausible(first) && isPlausible(second) ? wordCount : 0;
}
@Override
public PluginAnalysis analyzeSet(final AnalyzerContext context, final long matchCount, final long realSamples,
final String currentRegExp, final Facts facts, final FiniteMap cardinality, final FiniteMap outliers, final TokenStreams tokenStreams, final AnalysisConfig analysisConfig) {
if (realSamples > 10 && !averageLengthOK())
return PluginAnalysis.SIMPLE_NOT_OK;
if (getHeaderConfidence(context.getStreamName()) < 90 && realSamples > 10 && (100*bad)/realSamples > 1)
return PluginAnalysis.SIMPLE_NOT_OK;
return super.analyzeSet(context, matchCount, realSamples, currentRegExp, facts, cardinality, outliers, tokenStreams, analysisConfig);
}
}