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:
I think this is actually a good thing--makes our proposal look like a much more preferable alternative by comparison, makes our support in the process more important, and sets Harvey up as the Ralph Nader equivalent in the election to fix California's broken system---a potential spoiler.
Postion	Tokenization
1	I
2	think
3	this
4	is
5	actually
6	a
7	good
8	thing
9	--
10	makes
11	our
12	proposal
13	look
14	like
15	a
16	much
17	more
18	preferable
19	alternative
20	by
21	comparison
22	,
23	makes
24	our
25	support
26	in
27	the
28	process
29	more
30	important
31	,
32	and
33	sets
34	Harvey
35	up
36	as
37	the
38	Ralph
39	Nader
40	equivalent
41	in
42	the
43	election
44	to
45	fix
46	California's
47	California
48	's
49	broken
50	system
51	---
52	a
53	potential
54	spoiler
55	.
Position	Tokenization	UPOS	Head	Deprel
1	I	PRON	2	nsubj
2	think	VERB	0	root
3	this	PRON	8	nsubj
4	is	AUX	8	cop
5	actually	ADV	8	advmod
6	a	DET	8	det
7	good	ADJ	8	amod
8	thing	NOUN	2	ccomp
9	--	PUNCT	2	punct
10	makes	VERB	2	parataxis
11	our	PRON	12	nmod:poss
12	proposal	NOUN	13	nsubj
13	look	VERB	10	ccomp
14	like	ADP	19	case
15	a	DET	19	det
16	much	ADV	17	advmod
17	more	ADV	18	advmod
18	preferable	ADJ	19	amod
19	alternative	NOUN	13	obl
20	by	ADP	21	case
21	comparison	NOUN	13	obl
22	,	PUNCT	23	punct
23	makes	VERB	10	conj
24	our	PRON	25	nmod:poss
25	support	NOUN	23	obj
26	in	ADP	28	case
27	the	DET	28	det
28	process	NOUN	25	nmod
29	more	ADV	30	advmod
30	important	ADJ	23	xcomp
31	,	PUNCT	33	punct
32	and	CCONJ	33	cc
33	sets	VERB	10	conj
34	Harvey	PROPN	33	obj
35	up	ADP	33	compound:prt
36	as	ADP	40	case
37	the	DET	40	det
38	Ralph	PROPN	40	compound
39	Nader	PROPN	38	flat
40	equivalent	NOUN	33	obl
41	in	ADP	43	case
42	the	DET	43	det
43	election	NOUN	33	obl
44	to	PART	45	mark
45	fix	VERB	43	acl
46	California's	_	None	_
47	California	PROPN	49	nmod:poss
48	's	PART	46	case
49	broken	ADJ	49	amod
50	system	NOUN	45	obj
51	---	PUNCT	33	punct
52	a	DET	53	det
53	potential	ADJ	53	amod
54	spoiler	NOUN	33	parataxis
55	.	PUNCT	2	punct