- In conclusion, I would like to assure you, Mr Borrell Fontelles, and also the European Parliament, that the Commission will continue to make its best efforts to support all the multilateral initiatives that are aimed at a comprehensive and effective ban on cluster mines.
- Sammanfattningsvis vill jag försäkra Josep Borell Fontelles och Europaparlamentet om att kommissionen kommer att fortsätta att göra sitt bästa för att stödja alla multilaterala initiativ vars syfte är att införa ett omfattande och effektivt förbud mot klusterminor.
- We took part in the EU troika démarches carried out in key countries such as the United States of America, Japan, Brazil, South Korea, Canada, Pakistan and Ukraine, to promote the multilateral initiatives on cluster munitions in the framework of the Convention on Certain Conventional Weapons, and in particular a negotiation on a legally binding instrument addressing humanitarian concerns about cluster munitions.
- Vi deltog i EU-trojkans demarcher som genomfördes i viktiga länder såsom Förenta staterna, Japan, Brasilien, Sydkorea, Kanada, Pakistan och Ukraina för att främja de multilaterala initiativen om klusterbomber inom ramen för konventionen om konventionella vapen och framför allt en förhandling om ett lagligt bindande instrument för hantering av humanitär oro för klusterbomber.
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 = 45579 AND
t12.lemma_id = 33876 AND
t21.lemma_id = 48477 AND
t22.lemma_id = 33876),
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;
;