- Better quality and more accurate first decisions would save money through fewer costly appeals.
- Bättre kvalitet och mer korrekta första beslut skulle spara pengar genom färre dyra överklaganden.
- For example, by reducing the consumption of imported oil, not only do you save money, and you do not pay it to the oil-producing countries, but you also reduce CO2 emissions.
- Genom att exempelvis minska förbrukningen av importerad olja sparar man pengar som därmed inte kommer de oljeproducerande länderna till del, samtidigt som man minskar koldioxidutsläppen.
- At a time when the Commission, and indeed this Parliament, ought to be searching for, and bringing forward, proposals on how to save money, we are offered this report which suggests the completion of the Galileo satellite navigation system at an additional cost of EUR 1.9 billion in the next Multiannual Financial Framework.
- Vid en tidpunkt då kommissionen, och naturligtvis parlamentet, borde söka och lägga fram förslag om hur vi kan spara pengar, läggs detta betänkande fram med ett förslag om att slutföra satellitnavigeringssystemet Galileo till en merkostnad på 1,9 miljarder euro i nästa fleråriga budgetram.
show query
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 = 'dobj' AND
s2.val = 'OO' AND
t11.ctag = 'VERB' AND
t21.ctag = 'VERB' AND
t12.ctag = 'NOUN' AND
t22.ctag = 'NOUN' AND
t11.lemma_id = 31525 AND
t12.lemma_id = 38740 AND
t21.lemma_id = 11413 AND
t22.lemma_id = 2337),
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;
;