This　paper　describes　the　use　of　semantic　similarity　measures　based　on　distributed　representations　of　words,　sentences,　and　paragraphs　(so-called　＂embeddings＂)　to　assess　the　impact　of　supra-lexical　factors　on　eye-movement　data　from　early　readers　of　Chinese.　In　addition,　we　used　a　corpus-based　measure　of　surprisal　to　assess　the　impact　of　local　word　predictability.　Eye　movement　data　from　56　Chinese　students　were　collected　(a)　in　the　students＇　4th　grade　and　(b)　one　year　later　while　they　were　in　5th　grade.　Results　indicated　that　surprisal　and　some　text　similarity　measures　have　a　significant　impact　on　the　momentto-moment　processing　of　words　in　reading.　The　paper　presents　an　easy-to-use　set　of　tools　for　linking　the　low-level　aspects　of　fixation　durations　to　a　hierarchy　of　sentence-level　and　paragraph-level　features　that　can　be　computed　automatically.　The　study　is　the　first　attempt,　as　far　as　we　are　aware,　to　track　the　developmental　trajectory　of　these　influences　in　developing　readers　across　a　range　of　reading　abilities.　The　similarity-based　measures　described　here　can　be　used　(a)　to　provide　a　measure　of　reader　sensitivity　to　sentence　and　paragraph　cohesion　and　(b)　to　assess　specific　texts　for　their　suitability　for　readers　of　different　reading　ability　levels.