- One of the ways of meeting this scientific, industrial and commercial challenge is to make up the lost ground and to harmonize national legislations.
- Ett sätt att bemöta denna vetenskapliga, industriella och handelsrelaterade utmaning är att komma ifatt den nuvarande förseningen och harmonisera de nationella lagstiftningarna.
- Practical cooperation between the police, customs and justice authorities of our Member States is essential if we are to conduct an active campaign against the drug trade, but - as the President-in-Office is aware - it is equally essential to harmonize national legislation on the penalties for drug dealing and use, because in the absence of such harmonization there can be no effective action and no safety for any of our fellow citizens, and especially for the young.
- Ett faktiskt samarbete mellan våra länders polis-, tull- och rättsväsenden är nödvändigt för att aktivt kunna kämpa mot drogtrafiken, men som ni vet, herr ordförande, det är lika viktigt att harmonisera de europeiska lagstiftningar som avser bekämpningen av drogtrafik och användning av droger.
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 = 3379 AND
t12.lemma_id = 6485 AND
t21.lemma_id = 50434 AND
t22.lemma_id = 25910),
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;
;