AI map entities classes

This PR introduces logic which labels entities with their DBpedia
ontological classes. Using this logic, it creates a file which tags
every unique entity found for the AI map dataset with their respective
classes.

closes #120

src/bin/dbpedia/getClasses.mjs

@@ -0,0 +1,47 @@
+import { promises as fs } from 'fs';
+
+import { Command, InvalidArgumentError } from 'commander';
+import * as _ from 'lamb';
+
+import { arxliveCopy } from 'conf/config.mjs';
+import { getClasses } from 'dbpedia/requests.mjs';
+import { getEntities } from 'es/entities.mjs';
+
+const program = new Command();
+program.option(
+	'-d, --domain <domain>',
+	'ES domain on which to aggregate',
+	arxliveCopy
+);
+program.option('-i, --index <index>', 'ES index from which to get titles');
+program.option('-f, --path <path>', 'Path to file containing DBpedia titles');
+program.requiredOption('-o, --out <output>', 'Path of output file');
+
+program.parse();
+const options = program.opts();
+
+const main = async () => {
+	if (!options.index && !options.path) {
+		throw new InvalidArgumentError(`
+            You must specify either the index containing the DBpedia entities 
+            or a path to the file containing the entities\' titles`
+		);
+	}
+	if (options.index && options.path) {
+		throw new InvalidArgumentError(`
+            Ambigous input. Do you want to use the index or the file as input?`
+		);
+	}
+
+	// previous checks garauntee the following:
+	const titles = options.index
+		? await getEntities(options.index)
+		: JSON.parse(await fs.readFile(options.path));
+
+	const sample=titles.slice(100, 110);
+	console.log(sample);
+	console.log(await getClasses(sample, { depth: 10, squash: true, fullURI:true }));
+
+};
+
+main();