---
title: "Network statistics on early English Syntax: Structural criteria (2007)"
description: "The paper sets out an experimental design for studying how English syntax emerges in a child's speech using… 23 references."
authors: ["Bernat Corominas-Murtra"]
year: 2007
venue: "arXiv:0704.3708"
source: "https://arxiv.org/abs/0704.3708"
doi: "10.48550/arxiv.0704.3708"
arxiv: "0704.3708"
licence: "arXiv — no licence stated (read only)"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/corominas-murtra-2007-network-statistics-early-english-syntax/"
---
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# Network statistics on early English Syntax: Structural criteria

**Authors:** Bernat Corominas-Murtra · **Year:** 2007 · **Venue:** arXiv:0704.3708 · **Licence:** arXiv — no licence stated (read only)

**Links:** [Publisher's page](https://arxiv.org/abs/0704.3708) · [PDF](https://arxiv.org/pdf/0704.3708) · [DOI 10.48550/arxiv.0704.3708](https://doi.org/10.48550/arxiv.0704.3708) · [arXiv 0704.3708](https://arxiv.org/abs/0704.3708) · [OpenAlex](https://openalex.org/W1623342287)

**Citations:** 8 citations (OpenAlex, 2026-10-14)

## Summary
The paper sets out an experimental design for studying how English syntax emerges in a child's speech using complex-network tools. Adult notions of grammaticality would discard most early utterances, even though many of them clearly have structure. The author therefore proposes descriptive annotation criteria for deciding what counts as structured in early child grammar. These criteria assume a constituency hierarchy and a grammar built on lexico-thematic relations. Each accepted utterance is analysed into headed constituents, and those constituents are projected onto directed word-to-word links. Pooling the links across utterances yields a syntactic network whose nodes are lexical items. The work uses the PETER corpus from CHILDES, annotated with the DGA-Annotator. It also argues a theoretical point: such networks show the global usage patterns of a grammar, not its internal rules. The resulting annotation supports two analyses: statistics on the average size of structures, ⟨S⟩, and standard complexity measures on the network across successive acquisition stages. A small worked example shows the full pipeline.

## Key points
- Data come from the PETER corpus of the CHILDES database. The child's lines are pulled out with a PERL routine, wrapped in XML, and annotated in the DGA-Annotator.
- Arcs are built by a fixed procedure:
  - an arc runs from each complement to its phrase head;
  - when the complement is itself a phrase, the arc runs from the inner head to the outer head, which preserves merge order;
  - the head is the semantically most relevant item;
  - finite verbs head the sentence.
- The criteria cover both rejected and accepted productions. Accepted cases include missing arguments, "to be", infra-specified lexical items, first functional particles, duplicated function words, non-structural items and negation.
- Unintelligible tokens ("xxx", "0") are dropped. In the example, four structures of sizes 4, 2, 3 and 3 give ⟨S⟩ = 3, with 9 lexical nodes and 7 edges.
- Network measures include degree assortativity ρ. A negative ρ means the network is disassortative and a positive ρ means it is assortative.

## Interesting ideas
- The author replaces adult grammaticality with lenient, explicit criteria for when a fragment still counts as structured, so partial utterances are kept rather than thrown away.
- A headed binary constituency tree is turned into directed head-ward arcs, with inner heads linking to outer heads so the order of merging can be recovered.
- Statistics over the aggregated network describe how a grammar is used, not how it works internally, so global measures should not be read as evidence about specific rules.
- Average structure size measured per time slice gives a single, simple indicator of growing syntactic capacity.
- Unintelligible or empty tokens are filtered out explicitly before annotation, so placeholder symbols never become graph nodes.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (tree): The same approach could define which partial trees from noisy or fragmentary input are still worth keeping, instead of discarding sentences the parser cannot fully attach.
- **I2** (tree): This is a compact, explainable rule set for converting constituency-style treebanks into dependency arcs during UD dialect conversion.
- **I3** (learn): Corpus-level statistics of silver trees should be read as usage profiles, and parser rules should be checked with targeted negative controls instead.
- **I4** (learn): A per-text or per-checkpoint mean constituent size could serve as a cheap progress signal during self-play, or for grading the difficulty of training texts.
- **I5** (tokens): A dedicated placeholder or noise token class in the tokenizer would stop such markers from leaking into lemmas and trees.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [Universitat Pompeu Fabra](https://md.research.elamur.ai/free/en/universities/universitat-pompeu-fabra/) — University, Barcelona, Spain · 47 works · 11,723 citations
- [Institució Catalana de Recerca i Estudis Avançats](https://md.research.elamur.ai/free/en/ngos/institucio-catalana-de-recerca-i-estudis-avancats/) — Nonprofit, Barcelona, Spain · 6 works · 453 citations

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## Cite

Cite as: Bernat Corominas-Murtra. 2007. Network statistics on early English Syntax: Structural criteria. arXiv:0704.3708.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@misc{corominasmurtra2007network,
  title = {{Network statistics on early English Syntax: Structural criteria}},
  author = {Bernat Corominas-Murtra},
  year = {2007},
  doi = {10.48550/arxiv.0704.3708},
  eprint = {0704.3708},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.0704.3708}
}
```

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## References

23 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 1 November 2026*