Syntax Matters

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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. 1

• 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. 2

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. 3

C. The Property Graph Schism

The market shift toward Labelled Property Graphs (LPG) like Neo4j is a direct result of this syntactic failure. 4

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

The current standardization of RDF-star is an admission that standard Reification failed. 5

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. 6