- The key challenges for the month ahead will be continued support to Montenegro, the strengthening of the Serbian civil society and the Serbian media, support of the Kosovo elections and to UNMIK and support for regional integration.
- De viktigaste utmaningarna för den kommande månaden kommer att bli det fortsatta stödet till Montenegro, stärkandet av det serbiska civila samhället och serbisk media, stöd till valen i Kosovo och till UNMIK och stöd till regional integration.
- The European Union’s new strategy to promote sustainable development, as adopted by our heads of state or government in June 2006, quite rightly includes public health as one of the key challenges we face, the aim being to promote health without discrimination and to improve protection against the health risks that are now being posed, and all this has to be achieved - and I will come back to this - by means of robust preventive measures.
- I Europeiska unionens nya strategi för att främja hållbar utveckling som antogs av våra stats- och regeringschefer i juni 2006 ingår med all rätt folkhälsan som en av de viktigaste utmaningar vi står inför, och målet är att främja hälsa utan diskriminering och att förbättra skyddet mot de nuvarande hälsoriskerna, och allt detta måste åstadkommas genom kraftfulla förebyggande åtgärder, vilket jag ska återkomma till.
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 = 19851 AND
t12.lemma_id = 38744 AND
t21.lemma_id = 49451 AND
t22.lemma_id = 14863),
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;
;