How does complexity effect sentence processing?
Early transformational grammar proposed that sentences requiring more transformations (e.g., passives, negatives, object‑relative clauses) are harder to process.
subject relative and object relative clauses:
(10.5) The boy who chased the dog ran home -> subject relative
(10.6) The boy who the dog chased ran home -> object relative
Evidence for complexity effecting sentence processing
Sentence–picture matching: passives and negatives took longer.
Transformation tasks: more complex transformations → longer response times.
Memory tasks: sentences closer in transformational structure were more confusable and harder to remember
Critiques of experiments measuring how sentence complexity effects processing
These tasks don’t reflect natural comprehension.
People rarely transform sentences explicitly.
Exposure frequency (e.g., actives > passives) also matters.
What is the clausal hypothesis - how does this relate to how we process sentences?
The hypothesis: clauses are the basic units of analysis in language comprehension
Clause = a group of words in a sentence that includes a verb
The argument is that we chunk sentences into clauses in order to process them
How do click-location experiments provide evidence for the clasual hypothesis?
Participants given a printed version of a sentence. They then listened to the sentence and a click was inserted at a point that was in the middle of the word/ not a clear boundary. The participants then had to mark on the written sentence where they heard the click.
Finding = Clicks were mis‑located toward clause boundaries, suggesting perceptual segmentation into clauses.
Critiques / counter argument of the clausal hypothesis
Distinguish clausal structuring (segmenting) from clausal processing (processing only at boundaries).
Word‑monitoring studies show processing is incremental, not restricted to clause boundaries.
“Sentence processing does not need to wait until major structural boundaries but can take place in a cumulative way as a sentence is heard.”
What did findings show in regards to the clasual hypothesis versus cumulative facilitation for normal, anomalous and scrambled prose?
Normal prose = syntactically and semantically well formed
Anomalous prose = syntactically well-formed but has little meaning
Scrambled prose = neither syntactically nor semantically well-formed but consists of real words
Normal prose shows cumulative facilitation; Anomalous prose also shows some, but scrambled prose does not -> in sentences that are both syntactically and semantically well formed as more of the sentence is heard words can be responded to more rapidly. This shows the sentence is being processed as it is heard rather than just at clause/ syntactic boundaries
How do explicit syntactic markers help with sentence processing? What experiments show this?
Explicit markers (e.g., that, who, inflections) facilitate processing but these are often left out in English language.
Findings:
Phoneme monitoring where participant have to find certain phonemes in the sentence: faster when markers are present.
Eye‑tracking: complementiser ‘that’ reduces ambiguity (e.g., John knew (that) the answer was wrong).
Markers are frequent, short, and provide anchor points.
How do prosody and punctuation support sentence processing
Prosody and punctuation also act as structural cues:
Prosodic phrasing helps only when syntactically motivated.
Punctuation and line breaks influence interpretation and reading difficulty.
Can make it more difficult/ slower to read a sentence if there is a line break in an unnatural place
Discontinuous constituents
Discontinuous constituents (I.e. phrase the belongs together syntactically but gets spilt apart by other material in the sentence e.g. Rang …Extra information about who… up) are hard to process.
Structural preferences in readers
Readers show structural preferences, sometimes leading to misanalysis and the need to re-read when they realise their ‘prediction’ is not correct
Garden‑path sentences
What are they?
What can be added to help with them?
induce an initially plausible but incorrect parse.
Example:
“The horse raced past the barn fell.” Readers initially treat raced as a past‑tense verb, not a reduced relative.
Adding explicit syntactic markers can help us figure out what it means
“The horse which was raced past the barn fell.”
The sausage machine model (Frazier & Fodor):
The sausage machine is a parser it analyses sentences according to their syntactic structure
It builds a syntactic tree known as phrase marker incrementally.
The parser is deterministic (one structure at a time) -> contrast with parallel processing models where multiple interpretations can be entertained at the same time
It prefers simple structures and avoids leaving material unattached.
List the two key parsing strategies
Late closure
Minimal attachment
Late Closure
Attach new material to the current clause/phrase whenever possible.
In the sentences below people generally prefer the first one as it obeys late closure - ‘the driver’ is attached to the first clause.
Minimal Attachment
Build the structure using the fewest new nodes. In other words have the simplest structure possible.
The first sentence is easier because it doesn’t have the extra S node
Evidence for late closure and minimal attachment comes from..
Eye tracking
Eye‑tracking shows longer fixations and regressions when these preferred parses fail.
Right Association strategy
New material attaches to the lowest possible node, unless other strategies (minimal attachment and late closure) override it
Syntactic category ambiguity + strategies to over come it
Many words are category‑ambiguous (e.g., walk = noun/verb).
When structure doesn’t force a category, the parser may:
Delay attachment until disambiguation → faster reading during ambiguous region, slower at disambiguation (portion of the sentence that follows and make the ambiguous parts clear)
Or (in alternative models) build multiple structures in parallel and then choose
Eye‑tracking evidence supports delayed attachment in some cases
are parsing strategies universal?
Parsing strategies are universal, but their relative weighting differs across languages depending on cue reliability.
Difference in languages for sentence processing
English speakers rely on word order.
German speakers rely more on animacy.
Italian speakers rely on agreement morphology.
How different languages respond to relative clause attachment ambiguity
English prefers Late Closure (attach to the most recent noun).
Spanish prefers high attachment (attach to the first noun).
With three‑noun structures, both languages prefer Recency.