- As a result, those companies would no longer be tempted to engage in illegal activities.
- Då skulle detta slags företag inte längre lockas att syssla med olagliga verksamheter.
- The decision establishes an obligation to pass on information upon any EP official or agent who ‘becomes aware of evidence which gives rise to a presumption of the existence of possible cases of fraud, corruption or any other illegal activity detrimental to the interests of the Communities.’
- I beslutet fastställs informationsplikt för tjänstemän i Europaparlamentet som ”får kännedom om omständigheter som tyder på förekomst av eventuella fall av bedrägeri, korruption, eller annan olaglig verksamhet som riktar sig mot gemenskapernas intressen”.
- I shall certainly emphasise one essentially political aspect of it, which is the requirement to tackle the immigration issue by combining the need to stop the traffic in human beings and any kind of illegal activity with the absolute need for solidarity, and solidarity means first and foremost saving human lives in danger.
- Jag vill däremot betona en väsentligen politisk aspekt av detta, nämligen att vi måste gripa oss an invandringsfrågan genom att kombinera behovet av att stoppa människohandeln och alla slags olagliga verksamheter med det ovillkorliga behovet av solidaritet, och solidaritet innebär först och främst att rädda människor i fara.
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 = 'amod' AND
s2.val = 'AT' AND
t11.ctag = 'NOUN' AND
t21.ctag = 'NOUN' AND
t12.ctag = 'ADJ' AND
t22.ctag = 'ADJ' AND
t11.lemma_id = 7628 AND
t12.lemma_id = 6098 AND
t21.lemma_id = 26332 AND
t22.lemma_id = 31589),
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;
;