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:
Aunque precisó que "subir los impuestos y una ley sobre las 35 horas no son buenas noticias para, ni para el empleo ni para la evolución de la economía" española.
Postion	Tokenization
1	Aunque
2	precisó
3	que
4	"
5	subir
6	los
7	impuestos
8	y
9	una
10	ley
11	sobre
12	las
13	35
14	horas
15	no
16	son
17	buenas
18	noticias
19	para
20	,
21	ni
22	para
23	el
24	empleo
25	ni
26	para
27	la
28	evolución
29	de
30	la
31	economía
32	"
33	española
34	.
Position	Tokenization	UPOS	Head	Deprel
1	Aunque	SCONJ	2	mark
2	precisó	VERB	0	root
3	que	SCONJ	18	mark
4	"	PUNCT	18	punct
5	subir	VERB	18	csubj
6	los	DET	7	det
7	impuestos	NOUN	5	obj
8	y	CCONJ	10	cc
9	una	DET	10	det
10	ley	NOUN	5	conj
11	sobre	ADP	14	case
12	las	DET	13	det
13	35	NUM	14	nummod
14	horas	NOUN	10	nmod
15	no	ADV	18	advmod
16	son	AUX	18	cop
17	buenas	ADJ	18	amod
18	noticias	NOUN	2	ccomp
19	para	ADP	18	nmod
20	,	PUNCT	24	punct
21	ni	CCONJ	24	cc
22	para	ADP	24	case
23	el	DET	24	det
24	empleo	NOUN	19	conj
25	ni	CCONJ	28	cc
26	para	ADP	28	case
27	la	DET	28	det
28	evolución	NOUN	19	conj
29	de	ADP	31	case
30	la	DET	31	det
31	economía	NOUN	28	nmod
32	"	PUNCT	33	punct
33	española	ADJ	31	amod
34	.	PUNCT	2	punct