Syntax Matters

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⚠️ LLM-generated content notice: Parts of this page may have been created or edited with the assistance of a large language model (LLM). The prompts that have been used might be on the page itself, the discussion page or in straight forward cases the prompt was just "Write a mediawiki page on X" with X being the page name. While the content has been reviewed it might still not be accurate or error-free.

Syntax Matters and how RDF miserably fails

Prompt 2025-11-28 for Gemini3 Pro Preview

I would like to write a "syntax matters!" critique on the RDF world as a scientific paper. My argument starts with SiDIF (87,000 views), which expresses facts verbatim like dad loves mum. Why on earth should I write http://somedomain/somepath/dad ...? That leads to "query rot" when frameworks are mirrored or graphs split. The idea behind those IRIs is unique identification, which fails miserably in practice.

I also have high-traffic resources: SPARQL (230,000 views) and Gremlin (160,000 views). These view counts have increased massively in the past 3 years due to LLM scraping. Where should I start, and what is prior work?

Research Strategy Response

Your critique centers on three axes: **Syntactic Diffuseness** (verbosity), **Identifier Fragility** (query rot), and **Token Efficiency** (the LLM scraping perspective).

Phase 1: Theoretical Frameworks

To convert the `dad loves mum` argument into a scientific critique, apply these frameworks:

  • Cognitive Dimensions of Notations (Diffuseness):

Green's framework classifies notations by their information density. RDF's IRI structure creates extreme *Diffuseness* (too many symbols to express one fact). SiDIF acts as a counter-example of high-density notation. green1996usability

  • The "Global ID" Fallacy:

Your argument about "query rot" challenges the central dogma of the Semantic Web: that global identifiers (IRIs) are robust. In practice, separating identity from location breaks when graphs are mirrored (e.g., Development vs. Production environments).

Phase 2: The LLM & Token Efficiency Argument

The massive increase in view counts on your SPARQL, Gremlin, and SiDIF pages due to LLM scraping introduces a novel scientific argument: **Token Economics**.

  • Token Density vs. Verbosity:

LLMs are trained on text. Code that is verbose (RDF/XML or full IRIs) consumes more context window (tokens) for less semantic value than concise formats.

  • The Training Signal: The high scraping rate suggests these formats are becoming foundational "ground truth" for AI code generation. If SiDIF (`dad loves mum`) is more token-efficient than N-Triples (`<http://...> <http://...> <http://...>`), it represents a superior syntax for the AI era.

Phase 3: Prior Work & Literature Map

A. The "Mere Mortal" Barrier (Complexity)

The insistence on full IRIs is tied to the heavy logical foundations of OWL.

  • Incomprehensibility of the Stack: The rigorous naming is required for decision procedures like SROIQ (<math>\text{N2ExpTime}</math> complexity). This theoretical purity alienates developers and creates the "syntax friction" you observe. kazakov2008riq

B. The Imperative vs. Declarative Gap (Gremlin)

  • Marko's Paper (The Graph Traversal Pattern): Marko Rodriguez's work on Gremlin fundamentally opposes the RDF model. Gremlin's "Traversal" approach (`g.V().out('loves')`) avoids the rigidity of triplet pattern matching, aligning closer to your `dad loves mum` model. rodriguez2015gremlin

C. The Property Graph Schism

The market shift toward Labelled Property Graphs (LPG) like Neo4j is a direct result of this syntactic failure. angles2017foundations

D. The "Reification" Problem (RDF-star)

The current standardization of RDF-star is an admission that standard Reification failed. hartig2014re

E. The "Stealth" Approach (JSON-LD)

JSON-LD was an attempt to hide the IRIs that you critique, admitting that native RDF syntax was a barrier. sporny2014jsonld


{{#scite: |reference=green1996usability |type=journal-article |title=Usability analysis of visual programming environments: a ‘cognitive dimensions’ framework |authors=T.R.G. Green; M. Petre |publisher=Journal of Visual Languages & Computing |doi=10.1006/jvlc.1996.0009 |year=1996 }}

{{#scite: |reference=kazakov2008riq |type=article |title=RIQ and SROIQ are Harder than SHOIQ* |authors=Yevgeny Kazakov |publisher=AAAI |year=2008 }}

{{#scite: |reference=rodriguez2015gremlin |type=article |title=The Gremlin graph traversal machine and language |authors=Marko A. Rodriguez |publisher=Proceedings of the 15th Symposium on Database Programming Languages |doi=10.1145/2815072.2815073 |year=2015 }}

{{#scite: |reference=angles2017foundations |type=journal-article |title=The Foundations of Property Graph Query Languages |authors=Renzo Angles; Marcelo Arenas; Pablo Barceló; Aidan Hogan; Juan Reutter; Domagoj Vrgoč |publisher=ACM Computing Surveys |doi=10.1145/3104031 |year=2017 }}

{{#scite: |reference=hartig2014re |type=journal-article |title=Reconciliation of RDF* and Property Graphs |authors=Olaf Hartig |publisher=arXiv |doi=10.48550/ARXIV.1409.3288 |year=2014 |retrieved-from=https://doi.org/ |retrieved-on=2025-11-28 }}

{{#scite: |reference=sporny2014jsonld |type=article |title=JSON-LD 1.0: A JSON-based Serialization for Linked Data |authors=Manu Sporny; Gregg Kellogg; Markus Lanthaler |publisher=W3C Recommendation |year=2014 }}