- The means of payment for the PHARE and TACIS programmes, for former Yugoslavia and for the macro-economic aid for Macedonia can now be increased, that is to say they can now be safeguarded.
- Anslagen för programmen Phare, Tacis, för f.d. Jugoslavien samt för den makroekonomiska hjälpen till Makedonien kan höjas respektive säkras nu.
- The next item is the debate on the report by Mrs Neyts-Uyttebroeck, on behalf of the Committee on Foreign Affairs, on a proposal for a European Parliament recommendation to the Council on the mandate of the International Criminal Tribunal for the former Yugoslavia.
- Nästa punkt är en debatt om ett betänkande av Annemie Neyts-Uyttebroeck, för utskottet för utrikesfrågor, med ett förslag till Europaparlamentets rekommendation till rådet om uppdraget för Internationella krigsförbrytartribunalen för f.d. Jugoslavien.
- The present situation places us in the same condition of complicity with the worst of the worst, with the murderers and torturers, those that abused the right to life and attempted to destroy the law, as we witnessed from 1985 onwards in what was to become the former Yugoslavia.
- Den verklighet vi står inför gör oss till medbrottslingar med det onda, med mördarna och dem som torterar rätten till liv och det rättvisa livet och som vi har framför oss med all önskvärd tydlighet, sedan 1985, i det som blev f.d. Jugoslavien.
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 = 41317 AND
t12.lemma_id = 36087 AND
t21.lemma_id = 56176 AND
t22.lemma_id = 17408),
stats AS (SELECT
sentence_id,
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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;
;