- Lastly, we urge the government to remove all legal obstacles that still allow people to be marginalised, because of their sexual orientation, for instance.
- Slutligen uppmanar vi regeringen att undanröja alla rättsliga hinder som fortfarande tillåter marginalisering av personer, på grund av exempelvis sexuell läggning.
- This one-stop shop should aim to remove obstacles, especially arising from work-related social security questions, and to extend the knowledge of workers about their individual rights.
- Målet bör vara att undanröja hinder, särskilt när det gäller arbetsrelaterade socialförsäkringsfrågor, och öka arbetstagarnas kunskap om sina individuella rättigheter.
- I support this European Parliament report in general, and consider it crucial that EU actors give their all to removing obstacles to development, to achieving the MDG, to the fight against poverty, and to ensuring that human, social, economic and environmental rights are actually put into practice in developing countries.
- Jag stöder i allmänhet detta betänkande från parlamentet och anser att det är avgörande att EU:s aktörer gör allt för att undanröja hinder för utveckling, för att uppnå millennieutvecklingsmålen, för kampen mot fattigdom, och för att se till att mänskliga, sociala, ekonomiska och miljömässiga rättigheter faktiskt omsätts i praktiken i utvecklingsländerna.
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 = 14567 AND
t12.lemma_id = 38186 AND
t21.lemma_id = 37115 AND
t22.lemma_id = 31204),
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;
;