As a helpful and smart assistant, your task is to parse a given text in any language to Universal Dependency (UD) format including POS tags and dependency relations (HEAD and DEPREL).
Key Components of UD Annotation:
1. Tokens: The fundamental units within UD are tokens. These can be individual words, punctuation marks, or even parts of multi-word expressions. Each token has several associated attributes.
2. UPOS Tags: The UPOS field in the CoNLL-U format represents the universal part-of-speech tag assigned to each word. This tag is part of a universal POS tag set designed to be applicable across different languages. The UPOS tags include categories such as NOUN, VERB, ADJ (adjective), ADV (adverb), PRON (pronoun), DET (determiner), and more. 
3. Dependency Relations: Dependency relations are the core of the syntactic representation. They form a tree structure over the tokens in a sentence. Here's how they work:
    - HEAD: This field indicates the head of the current word. The head is the word that the current word is connected to in the dependency parse tree. The value is an integer that corresponds to the ID of the head word within the same sentence. A value of zero (0) indicates that the word is the root of the sentence.
    - DEPREL: The DEPREL field specifies the type of dependency relation between the current word and its head (as specified in the HEAD field). The value is a universal dependency relation or a language-specific subtype of such a relation.
Note: Blank lines are used to mark the boundaries between sentences.
Example:
Let's analyze this sentence with its UD annotation:
"The big dog chased the cat."
1. Tokenization:
- The
- big
- dog
- chased
- the
- cat
- .
2. UPOS Tags:
- The: DET
- big: ADJ
- dog: NOUN
- chased: VERB
- the: DET
- cat: NOUN
- .: PUNCT
3. Head node (parent):
- The: the parent of this word is "dog" at position 3
- big: the parent of this word is "dog" at position 3
- dog: the parent of this word is "chased" at position 4
- chased: this is the root node, therefore its head is 0
- the: the parent of this word is "cat" at position 6
- cat: the parent of this word is "chased" at position 4
- .: the parent of this word is "chased" at position 4
3. Dependency Relations:
- root(ROOT, chased)
- det(dog, The)
- amod(dog, big)
- nsubj(chased, dog)
- det(cat, the)
- obj(chased, cat)
Combining the above annotations, the final output in UD format is:
Position	Tokenization	UPOS	Head	Deprel
1	The	DET	3	det
2	big	ADJ	3	amod
3	dog	NOUN	4	nsubj
4	chased	VERB	0	ROOT
5	the	DET	6	det
6	cat	NOUN	4	obj
7	.	PUNCT	4	punct
Generate UD annotations for the following tokenized text:
Triadú detalló hoy, durante unas jornadas sobre la situación tecnológica de Cataluña, que a tal efecto se reunieron el mes pasado en Seattle (Estados Unidos) el presidente ejecutivo de Microsoft, Steve Ballmer, y el consejero de Industria de la Generalitat, Antoni Subirá.
Postion	Tokenization
1	Triadú
2	detalló
3	hoy
4	,
5	durante
6	unas
7	jornadas
8	sobre
9	la
10	situación
11	tecnológica
12	de
13	Cataluña
14	,
15	que
16	a
17	tal
18	efecto
19	se
20	reunieron
21	el
22	mes
23	pasado
24	en
25	Seattle
26	(
27	Estados
28	Unidos
29	)
30	el
31	presidente
32	ejecutivo
33	de
34	Microsoft
35	,
36	Steve
37	Ballmer
38	,
39	y
40	el
41	consejero
42	de
43	Industria
44	de
45	la
46	Generalitat
47	,
48	Antoni
49	Subirá
50	.
Position	Tokenization	UPOS	Head	Deprel
1	Triadú	PROPN	2	nsubj
2	detalló	VERB	0	root
3	hoy	ADV	2	advmod
4	,	PUNCT	7	punct
5	durante	ADP	7	case
6	unas	DET	7	det
7	jornadas	NOUN	2	obl
8	sobre	ADP	10	case
9	la	DET	10	det
10	situación	NOUN	7	nmod
11	tecnológica	ADJ	10	amod
12	de	ADP	13	case
13	Cataluña	PROPN	10	nmod
14	,	PUNCT	7	punct
15	que	SCONJ	20	mark
16	a	ADP	18	case
17	tal	DET	18	det
18	efecto	NOUN	20	obl
19	se	PRON	20	obj
20	reunieron	VERB	2	ccomp
21	el	DET	22	det
22	mes	NOUN	20	obl
23	pasado	ADJ	22	amod
24	en	ADP	25	case
25	Seattle	PROPN	20	obl
26	(	PUNCT	27	punct
27	Estados	PROPN	25	flat
28	Unidos	PROPN	27	flat
29	)	PUNCT	27	punct
30	el	DET	31	det
31	presidente	NOUN	20	nsubj
32	ejecutivo	ADJ	31	amod
33	de	ADP	34	case
34	Microsoft	PROPN	31	nmod
35	,	PUNCT	36	punct
36	Steve	PROPN	31	appos
37	Ballmer	PROPN	36	flat
38	,	PUNCT	36	punct
39	y	CCONJ	41	cc
40	el	DET	41	det
41	consejero	NOUN	31	conj
42	de	ADP	43	case
43	Industria	PROPN	41	nmod
44	de	ADP	46	case
45	la	DET	46	det
46	Generalitat	PROPN	41	nmod
47	,	PUNCT	48	punct
48	Antoni	PROPN	41	appos
49	Subirá	PROPN	48	flat
50	.	PUNCT	2	punct