- The other structural need derives from the very fact that enlargement is imminent.
- Det andra strukturella behovet härrör från den nära förestående utvidgningen.
- The results are derived from models and have not been validated by real field data.
- Resultaten härrör från förebilder och har inte bekräftats genom verkliga fältuppgifter.
- All this will be of vital importance in allowing them to respond dynamically to the challenges of the future, whether these derive from imports from non-EU countries or from new technological developments in the use of by-products.
- Allt detta är av störst vikt för att de ska kunna svara upp mot framtida utmaningar på ett dynamiskt sätt, vare sig dessa härrör från import från länder utanför EU eller från nya tekniska landvinningar för användningen av biprodukter.
- If we do not support the amendments from the Committee on Legal Affairs, this regulation would de facto promote the development of products derived from embryonic stem cells, although this might be considered as ethically unacceptable by citizens and Member States.
- Om vi inte stöder ändringsförslagen från utskottet för rättsliga frågor skulle förordningen i själva verket främja utvecklingen av läkemedel som härrör från embryonala stamceller, trots att somliga medborgare och medlemsstater anser att detta är etiskt oacceptabelt.
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 = 49354 AND
t12.lemma_id = 15442 AND
t21.lemma_id = 21349 AND
t22.lemma_id = 58308),
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;
;