上次说过，绝大多数的parsers对于谓词的 subcat 的表达都很简陋，伸展不开，多数不过把 subcat 当成一个代码，然后在相关的 subcat 规则中去确定 pattern。但是词驱动的文法 HPSG 却可以丝丝入扣，合情合理，可以直接在词典里面把 subcat 的 pattern 细致地描述，并对其句法语义的输入（pattern的条件）和输出（逻辑语义）之间的映射和解构，做出一个符合语言学原则的表达（representation）。
简陋有简陋的工程考量和理由，叠床架屋有叠床架屋的逻辑优美。鱼与熊掌不可兼得，我们最终还是更加倾向于简陋之法。尽管如此，走简陋快捷的路线的人，如果对结构表达的优美有所体验，还是有莫大的好处，至少不会被简陋的表象所迷惑，对于复杂的语言现象，逐渐摆脱简陋的捉襟见肘。
最近回看当年博士阶段的涂鸦文章，虽然其中反映出的对汉语句法的见识并不出彩，但是得力于 HPSG 的结构丰富性，还是把 subcat 在汉语文法中应用，表现得有条不紊，经得起时间的检验。当年钻研 HPSG 还是很专心的，吃得蛮透。正因为吃得透了，后来扬弃的时候就没有拖泥带水的牵挂。
譬如，在论及汉语NP带坑的现象的时候，是这样模型的：
11a) 桌子坏了。
11b) 腿坏了。
11c) 桌子的腿坏了。
12a) 他好。
12b) 身体好。
12c) 他的身体好。When people say 11b) tui huai le (leg went wrong), we know something (the possessor) is omitted. For 11a), however, we have no such feel of incompleteness.
Although we may also ask whose table, this possessive relation between who and table is by no means innate. Similarly, ta (he) in 12a) is a complete notion denoting someone while shenti (body) in 12b) is not. In 11c) and 12c), the possessor appears in the possessive structure DE-construction, the expectation of tui (leg) and shenti (body) is realized. These examples show that some words (concepts) have conceptual expectation for some other words (concepts) although the expected words do not necessarily show up in a sentence and the expectation might not be satisfied. In fact, this type of expectation forms part of our knowledge (common sense). One way to represent the knowledge is to encode it with the related word in the lexicon.
Therefore we propose an underlying SYNSEM feature KNOWLEDGE to store some of our common sense knowledge by capturing the internal relation between concepts. KNOWLEDGE parallels to syntactic SUBCAT and semantic RELATION. KNOWLEDGE imposes semantic constraints on their expected arguments no matter what syntactic forms the arguments will take (they may take null form, i.e. the underlying arguments are not realized). In contrast, SUBCAT only defines syntactic requirement for the complements and gets interpreted in RELATION. Following this design, syntactic form and semantic constraints are kept apart. When necessary, the interaction between them can be implemented by lexical rules, or directly coindexed in the lexicon. For example, the following KNOWLEDGE information will be enforced as the necessary semantic constraints when we handle Chinese NP predicates by a lexical rule (see 3.3).
把常识暗度陈仓从后门带入文法，就是从那时候开始的。这个做法在欧洲语言的形式文法中不多见，因为句法形式大体够用了，通常不需要常识的帮忙。但是对于汉语，没有某种常识的引入，想做一个成熟的深度分析系统，则很难。当年带常识的的句法结构模型是这样定义的：
PHON shenti
SYNSEM | KNOWLEDGE | PRED [1] possess
SYNSEM | KNOWLEDGE | POSSESSOR [2] human
SYNSEM | KNOWLEDGE | POSSESSED [3]
SYNSEM | LOCAL | CONTENT | INDEX [3]
SYNSEM | LOCAL | CONTENT | RESTRICTION { RELATION body }
SYNSEM | LOCAL | CONTENT | RESTRICTION { INSTANCE [3] }
最后，汉语文法中常识的引入被认为是对欧洲语言利用性数格的 agreement 的一个自然延伸。句法手段到语义限制的延伸。
Agreement revisited
This section relates semantic constraints which embody common sense to the conventional linguistic notion of agreement. We will show that they are essentially the same thing from different perspectives. We only need slight expansion for the definition of agreement to accommodate some of our basic knowledge. This is important as it accounts for the feasibility of coding knowledge in linguistic ways. Linguistic lexicon seems to be good enough to house some general knowledge in addition to linguistic knowledge.
为 parse“我鸡吃“ 和“鸡我吃”， 常识进入了文法（现在也可以利用大数据把常识代入）：
A typical example of how concepts are linked in a network (a sophisticated concept lexicon) is seen in the representation of drink ((*ANI SUBJ) (((FLOW STUFF) OBJE) ((SELF IN) (((*ANI (THRU PART)) TO) (BE CAUSE))))) in Wilks 1975b. While for various reasons we will not go as far as Wilks, we can gain enlightenment from this type of AI approach to knowledge. Lexicon-driven systems like the one in HPSG can, of course, make use of this possibility. Take the Chinese role-assignment problem, for example, the common sense that ANIMATE being eats FOOD can be seamlessly incorporated in the lexical entry chi (eat) as a semantic agreement requirement.
PHON chi
SYNSEM | KNOWLEDGE | PRED [1] eat
SYNSEM | KNOWLEDGE | AGENT [2] animate
SYNSEM | KNOWLEDGE | PATIENT [3] food
SYNSEM | LOCAL | CATEGORY | SUBCAT | EXTERNAL_ARGUMENT [NP: [4]]
SYNSEM | LOCAL | CATEGORY | SUBCAT | INTERNAL_ARGUMENTS <[NP: [5]]>
SYNSEM | LOCAL | CONTENT | RELATION [1]
SYNSEM | LOCAL | CONTENT | EATER [4] | INDEX | ROGET [2]
SYNSEM | LOCAL | CONTENT | EATEN [5] | INDEX | ROGET [3]
可见，看上去不过是 POS 细分后的一个 subcat 的代码，里面其实包含了多少结构及其蕴含其内的知识。在 unification grammars 几乎成为历史陈迹的今天，我还是认为 HPSG 这样的表达是最优美的语言学的逻辑表达之一，论逻辑的清晰和美，后来的文法很难超越。
[Related]
Handling Chinese NP predicate in HPSG （old paper）
Notes for An HPSG-style Chinese Reversible Grammar
Outline of an HPSG-style Chinese reversible grammar
PhD Thesis: Morpho-syntactic Interface in CPSG (cover page)
Overview of Natural Language Processing
Dr. Wei Li’s English Blog on NLP
