• However, this is exactly what we are doing with the texts which have been tabled in the so-called ’joint motion for a resolution’.
• Men det är just det vi åstadkommer med de texter som har lagts fram i detta så kallade ”gemensamma förslag till resolution”.

• What we are doing with European regional and structural policy is, indeed, also aid, albeit not of the State variety that we want to discuss this evening, and those policies are political instruments in supporting SMEs, environmental protection, research and development.
• Det vi åstadkommer med hjälp av den europeiska regional- och strukturpolitiken är ju också stöd, även om det inte är det statliga stöd, som vi i kväll skall diskutera, och den är ett politiskt handlingsinstrument för att stödja små och medelstora företag samt miljöskydd, liksom forskning och utveckling.

SET search_path TO f9miniensv;

WITH
	list AS (SELECT
		         t11.token_id AS t11,
		         t12.token_id AS t12,
		         t21.token_id AS t21,
		         t22.token_id AS t22,
		         r1.dep_id AS dep1,
		         r2.dep_id AS dep2
		         FROM
			         deprel r1
			         JOIN depstr s1 ON s1.dep_id = r1.dep_id
			         JOIN word_align a1 ON a1.wsource = r1.head AND a1.wsource < a1.wtarget
			         JOIN word_align a2 ON a2.wsource = r1.dependent
			         JOIN deprel r2 ON r2.head = a1.wtarget AND r2.dependent = a2.wtarget
			         JOIN depstr s2 ON s2.dep_id = r2.dep_id
			         JOIN token t11 ON t11.token_id = r1.head
			         JOIN token t21 ON t21.token_id = r2.head
			         JOIN token t12 ON t12.token_id = r1.dependent
			         JOIN token t22 ON t22.token_id = r2.dependent
		         WHERE
				         s1.val = 'prep' AND
				         t11.ctag = 'VERB' AND
				         t21.ctag = 'VERB' AND
				         t12.ctag = 'ADP' AND
				         t22.ctag = 'ADP' AND
				         t11.lemma_id = 27461 AND
				         t12.lemma_id = 12425 AND
				         t21.lemma_id = 10087 AND
				         t22.lemma_id = 57357),
	stats AS (SELECT
		          sentence_id,
		          count(DISTINCT token_id) AS c,
		          count(*) AS c_aligned,
		          count(DISTINCT wtarget) AS c_target
		         FROM
			         token
			         LEFT JOIN word_align ON wsource = token_id
		         WHERE
				         sentence_id IN (
					                        SELECT sentence_id
						                        FROM
							                        list
							                        JOIN token ON token_id IN(t11, t21)
					                        )
		         GROUP BY sentence_id),
	numbered AS (SELECT row_number() OVER () AS i, *
		         FROM
			         list),
	sentences AS (SELECT *, .2 * (1 / (1 + exp(max(c) OVER (PARTITION BY i) - min(c) OVER (PARTITION BY i)))) +
			                        .8 * (1 / log(avg(c) OVER (PARTITION BY i))) AS w
		         FROM
			         (
				         SELECT i, 1 AS n, sentence_id, ARRAY[t11,t12] AS tokens
					         FROM
						         numbered
						         JOIN token ON token_id = t11
				         UNION SELECT i, 2 AS n, sentence_id, ARRAY[t21,t22] AS tokens
					         FROM
						         numbered
						         JOIN token ON token_id = t21
				         ) x
			         JOIN stats USING (sentence_id)
		         ORDER BY i, n)
	SELECT
		i,
		n,
		w,
		c,
		c_aligned,
		c_target,
		sentence_id,
		string_agg(CASE WHEN lpad THEN ' ' ELSE '' END || '<span class="token' ||
			           CASE WHEN ARRAY[token_id] <@ tokens THEN ' hl' ELSE '' END || '">' || val || '</span>',
		           '' ORDER BY token_id ASC) AS s
	FROM
		sentences
		JOIN token USING (sentence_id)
		JOIN typestr USING (type_id)
	GROUP BY i, n, w, c, c_aligned, c_target, sentence_id
	ORDER BY w DESC, i, n;
;