Pith Number

pith:H6INDLDW

pith:2026:H6INDLDWF5GVBMZLV5AHJXU6FJ

not attested not anchored not stored refs resolved

A Hybrid Framework for Natural Language Querying of IFC Models with Relational and Graph Representations

Haowen Xu, Johnson Xuesong Shen, Rabindra Lamsal, Sisi Zlatanova, Yafei Sun

Transforming IFC models into relational tables and graphs lets an LLM answer natural language queries about building data with over 93 percent first-attempt accuracy.

arxiv:2605.13236 v1 · 2026-05-13 · cs.CL

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\usepackage{pith}
\pithnumber{H6INDLDWF5GVBMZLV5AHJXU6FJ}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

combining complementary representations with iterative reasoning enables more accessible natural language querying of IFC data while supporting routine BIM analysis tasks.

C2weakest assumption

The transformations to relational and graph representations preserve all information needed for accurate querying, and the LLM can reliably detect and correct its own errors through iteration without introducing new inaccuracies.

C3one line summary

IfcLLM combines relational and graph representations of IFC models with iterative LLM reasoning to deliver 93.3-100% first-attempt accuracy on natural language queries across three test models.

References

88 extracted · 88 resolved · 5 Pith anchors

[1] C. M. Eastman, BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors, John Wiley & Sons,

[2] doi:10.1002/9781119287568 · doi:10.1002/9781119287568

[3] H. Wang, Y. Pan, X. Luo, Integration of bim and gis in sustainable built environment: A review and bibliometric analysis, Automation in construction 103 (2019) 41–52. doi:10.1016/j.autcon.2019.03.005 2019 · doi:10.1016/j.autcon.2019.03.005

[4] A. Alattas, E. Kalogianni, T. Alzahrani, S. Zlatanova, P. van Oosterom, Map- ping private, common, and exclusive common spaces in buildings from bim/ifc to ladm. a case study from saudi arabia, Land U 2021 · doi:10.1016/j.landusepol.2021.105355

[5] L. Liu, B. Li, S. Zlatanova, P. van Oosterom, Indoor navigation supported by the industry foundation classes (ifc): A survey, Automation in Construction 121 (2021) 103436. doi:10.1016/j.autcon.2020.10 2021 · doi:10.1016/j.autcon.2020.103436

Receipt and verification

First computed	2026-05-18T02:44:49.545185Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

3f90d1ac762f4d50b32baf4074de9e2a59841cc5921b97e36d03cacedc62688d

Aliases

arxiv: 2605.13236 · arxiv_version: 2605.13236v1 · doi: 10.48550/arxiv.2605.13236 · pith_short_12: H6INDLDWF5GV · pith_short_16: H6INDLDWF5GVBMZL · pith_short_8: H6INDLDW

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/H6INDLDWF5GVBMZLV5AHJXU6FJ \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 3f90d1ac762f4d50b32baf4074de9e2a59841cc5921b97e36d03cacedc62688d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "c7cb25196997d81cf2c32c3d17cdf0197232fb6aff5adeb7a2f41a43a7729dfc",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-05-13T09:24:51Z",
    "title_canon_sha256": "fe79062cdf076f9644c3d32ed6cb8bca93db15e8b31c9e33624e587158396817"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13236",
    "kind": "arxiv",
    "version": 1
  }
}