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 segunda ocasión en los últimos tres años el fantasma de las lesiones en las rodillas de los peloteros volvió a causar mella en el equipo titular de los Astros de Houston.
Postion	Tokenization
1	Por
2	segunda
3	ocasión
4	en
5	los
6	últimos
7	tres
8	años
9	el
10	fantasma
11	de
12	las
13	lesiones
14	en
15	las
16	rodillas
17	de
18	los
19	peloteros
20	volvió
21	a
22	causar
23	mella
24	en
25	el
26	equipo
27	titular
28	de
29	los
30	Astros
31	de
32	Houston
33	.
Position	Tokenization	UPOS	Head	Deprel
1	Por	ADP	3	case
2	segunda	ADJ	3	amod
3	ocasión	NOUN	20	obl
4	en	ADP	8	case
5	los	DET	8	det
6	últimos	ADJ	5	amod
7	tres	NUM	5	nummod
8	años	NOUN	3	nmod
9	el	DET	10	det
10	fantasma	NOUN	20	nsubj
11	de	ADP	13	case
12	las	DET	13	det
13	lesiones	NOUN	10	nmod
14	en	ADP	16	case
15	las	DET	16	det
16	rodillas	NOUN	13	nmod
17	de	ADP	19	case
18	los	DET	19	det
19	peloteros	NOUN	16	nmod
20	volvió	VERB	0	root
21	a	ADP	22	mark
22	causar	VERB	20	xcomp
23	mella	NOUN	20	obj
24	en	ADP	26	case
25	el	DET	26	det
26	equipo	NOUN	20	obl
27	titular	ADJ	26	amod
28	de	ADP	30	case
29	los	DET	30	det
30	Astros	PROPN	26	nmod
31	de	ADP	32	case
32	Houston	PROPN	30	flat
33	.	PUNCT	20	punct