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:
La señora Aguirre es una portera amargada y revenida que pone sus ordenanzas municipales y sus limpiasuelos abrasivos al servicio de esta especie de Tercer Reich antisindical en el que lleva camino de convertirse, no sólo en Madrid, la Operación Limpieza.
Postion	Tokenization
1	La
2	señora
3	Aguirre
4	es
5	una
6	portera
7	amargada
8	y
9	revenida
10	que
11	pone
12	sus
13	ordenanzas
14	municipales
15	y
16	sus
17	limpiasuelos
18	abrasivos
19	al
20	servicio
21	de
22	esta
23	especie
24	de
25	Tercer
26	Reich
27	antisindical
28	en
29	el
30	que
31	lleva
32	camino
33	de
34	convertirse
35	convertir
36	se
37	,
38	no
39	sólo
40	en
41	Madrid
42	,
43	la
44	Operación
45	Limpieza
46	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	señora	NOUN	6	nsubj
3	Aguirre	PROPN	2	appos
4	es	AUX	6	cop
5	una	DET	6	det
6	portera	NOUN	0	root
7	amargada	ADJ	6	amod
8	y	CCONJ	9	cc
9	revenida	ADJ	7	conj
10	que	PRON	11	nsubj
11	pone	VERB	6	acl
12	sus	DET	13	det
13	ordenanzas	NOUN	11	obj
14	municipales	ADJ	13	amod
15	y	CCONJ	17	cc
16	sus	DET	17	det
17	limpiasuelos	NOUN	13	conj
18	abrasivos	ADJ	17	amod
19	al	ADP	20	case
20	servicio	NOUN	11	obl
21	de	ADP	23	case
22	esta	DET	23	det
23	especie	NOUN	20	nmod
24	de	ADP	25	case
25	Tercer	PROPN	23	nmod
26	Reich	PROPN	25	flat
27	antisindical	ADJ	25	amod
28	en	ADP	30	case
29	el	DET	30	det
30	que	PRON	31	iobj
31	lleva	VERB	25	acl
32	camino	NOUN	31	compound
33	de	ADP	34	mark
34	convertirse	_	None	_
35	convertir	VERB	31	xcomp
36	se	PRON	34	expl:pv
37	,	PUNCT	38	punct
38	no	ADV	38	advmod
39	sólo	ADV	31	advmod
40	en	ADP	38	case
41	Madrid	PROPN	38	nmod
42	,	PUNCT	38	punct
43	la	DET	43	det
44	Operación	PROPN	31	nsubj
45	Limpieza	PROPN	43	flat
46	.	PUNCT	6	punct