- The EU will voluntarily sacrifice an important shop window for its branded export goods, and the tourist trade will suffer demonstrable damage.
- EU offrar frivilligt ett viktigt skyltfönster för sina märkesexportartiklar, och turistbranschen lider påvisbara skador.
- ’Deplores the fact that some mainstream parties have seen fit to give credibility and acceptance to extremist parties by entering into coalition agreements, thereby sacrificing their moral integrity for the sake of short-term political gain and expediency.’
- ”Europaparlamentet beklagar att vissa mittenpartier har gett trovärdighet åt och accepterat extremistiska partier genom att ingå koalitioner och därmed offrat sin moraliska integritet för kortsiktiga politiska mål och kortsiktig nytta.”
- At any rate, I hope my speech will make my fellow Members think carefully about a complex issue that involves human beings - not just those human beings who are hoping for new kinds of treatment, but also those whose bodies and very lives might be sacrificed for the sake of others.
- Hur som helst hoppas jag att mitt anförande kommer att få mina kolleger i parlamentet att noga tänka igenom denna komplexa fråga som rör människor, inte bara de människor som hoppas på nya typer av behandlingar, utan också de vars kroppar och liv kan komma att offras för andras.
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 = 'prep' AND
t11.ctag = 'VERB' AND
t21.ctag = 'VERB' AND
t12.ctag = 'ADP' AND
t22.ctag = 'ADP' AND
t11.lemma_id = 4568 AND
t12.lemma_id = 36421 AND
t21.lemma_id = 55508 AND
t22.lemma_id = 64468),
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;
;