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:
Por su propia situación de víctima, ésta tendía a identificarse con Florentino Ariza, olvidándose incluso de que quizás Lorenzo Daza la había hecho venir para que influyera en favor del doctor Urbino.
Postion	Tokenization
1	Por
2	su
3	propia
4	situación
5	de
6	víctima
7	,
8	ésta
9	tendía
10	a
11	identificarse
12	identificar
13	se
14	con
15	Florentino
16	Ariza
17	,
18	olvidándose
19	olvidando
20	se
21	incluso
22	de
23	que
24	quizás
25	Lorenzo
26	Daza
27	la
28	había
29	hecho
30	venir
31	para
32	que
33	influyera
34	en
35	favor
36	del
37	doctor
38	Urbino
39	.
Position	Tokenization	UPOS	Head	Deprel
1	Por	ADP	4	case
2	su	DET	4	det
3	propia	DET	2	det
4	situación	NOUN	9	obl
5	de	ADP	6	case
6	víctima	NOUN	4	nmod
7	,	PUNCT	4	punct
8	ésta	PRON	9	nsubj
9	tendía	VERB	0	root
10	a	ADP	11	mark
11	identificarse	_	None	_
12	identificar	VERB	9	xcomp
13	se	PRON	11	obj
14	con	ADP	14	case
15	Florentino	PROPN	11	obl
16	Ariza	PROPN	14	flat
17	,	PUNCT	17	punct
18	olvidándose	_	None	_
19	olvidando	VERB	9	advcl
20	se	PRON	17	expl:pv
21	incluso	ADV	17	advmod
22	de	ADP	27	mark
23	que	SCONJ	27	mark
24	quizás	ADV	27	advmod
25	Lorenzo	PROPN	27	nsubj
26	Daza	PROPN	23	flat
27	la	PRON	27	obj
28	había	AUX	27	aux
29	hecho	VERB	17	xcomp
30	venir	VERB	27	xcomp
31	para	ADP	31	mark
32	que	SCONJ	31	mark
33	influyera	VERB	28	advcl
34	en	ADP	33	case
35	favor	NOUN	31	obl
36	del	ADP	35	case
37	doctor	NOUN	33	nmod
38	Urbino	PROPN	35	appos
39	.	PUNCT	9	punct