# MolP2SBench MolP2SBench Usual molecular benchmarks give a complete structure and ask for a property. MolP2SBench studies the inverse problem: a fragment of the molecule is hidden, and the system must decide which chemically valid completion fits the remaining graph and the supplied physical evidence. The work is a test of property-grounded completion. A high recovery rate can come from valence, common functional-group templates, or SMILES familiarity. The released views ask a narrower question: when several completions are already valid on the same scaffold, does the supplied property change the selection in the direction the evidence implies? ## Task The task is defined on molecular graphs and shown as SMILES. A connected functional group is replaced by a mask token. The system receives: - the masked SMILES and mask metadata - a short list of completed candidate SMILES, all valid on that scaffold - the properties listed for that directory It returns one candidate index. The closed comparison supplies that task text only: no tools, and no web search or literature retrieval. | Artifact | Path | | ------------- | ----------------------------------------------------------- | | Single-property prompt | `prompts/single_property_system.txt`, `prompts/single_property_user.txt` | | Bundle prompt | `prompts/property_bundle_system.txt`, `prompts/property_bundle_user.txt` | | All-properties prompt | `prompts/all_properties_system.txt`, `prompts/all_properties_user.txt` | | Tasks | `data//{correct,shuffled,counterfactual}.jsonl` | | Labels | `data//{correct,shuffled,counterfactual}.labels.jsonl` | Each task line is one JSON object with `record_id`, `masked_smiles`, `mask`, `properties`, and `candidate_completed_smiles`. The answer is not in that object. It is the sibling file `.labels.jsonl`. A label line has `record_id` and `label`. `label` is the 0-based index of the target candidate. The returned object matches the prompt: ```json { "record_id": "", "selected_candidate_index": 0, "reasoning": "" } ``` `selected_candidate_index` is a 0-based index into `candidate_completed_smiles`, in the order given. Single-property directories carry one representation. A bundle carries one family. `all_properties` carries seven properties: the dipole norm, the gap, infrared, Raman, ultraviolet–visible, proton NMR with integration, and carbon NMR with degeneracy. | Directory | Property | | ------------------------ | ------------------------------------------------------------------------- | | `dipole` | Dipole moment, Euclidean norm | | `gap` | Gap between the highest occupied and lowest unoccupied molecular orbitals | | `infrared` | Infrared spectrum | | `raman` | Raman spectrum | | `ultraviolet_visible` | Ultraviolet–visible excitations | | `proton_nmr_peaks` | Proton NMR, peaks only | | `proton_nmr_integration` | Proton NMR, peaks with integration | | `proton_nmr_atom` | Proton NMR, atom-wise | | `carbon_nmr_peaks` | Carbon NMR, peaks only | | `carbon_nmr_degeneracy` | Carbon NMR, peaks with degeneracy | | `carbon_nmr_atom` | Carbon NMR, atom-wise | | `electronic` | Dipole norm, gap, and ultraviolet–visible | | `magnetic_resonance` | Proton NMR with integration, and carbon NMR with degeneracy | | `vibrational` | Infrared and Raman spectra | | `all_properties` | The seven properties listed above | Correct and shuffled files have 136 records each. Counterfactual files have 240 records for dipole, infrared, Raman, ultraviolet–visible, `electronic`, `vibrational`, and `all_properties`. They have 258 records for the gap, each NMR representation, and `magnetic_resonance`. ## Views Exact match on the correct-property view is not evidence that the property was used. The same scaffolds are released under three views: | View | File | What is supplied | What it tests | | ----------------------- | ---------------------- | ------------------------------------------------------------- | ----------------------------------------------- | | Correct property | `correct.jsonl` | The property of the source molecule | Recovery under the matched property | | Shuffled property | `shuffled.jsonl` | The same property type, taken from a different molecule | Whether the value is read or ignored | | Counterfactual property | `counterfactual.jsonl` | The property of another valid completion on the same scaffold | Whether the choice moves toward that completion | Correct and shuffled views of a property share `record_id` and the candidate list. The shuffled file changes the property, not the answer index. A structure-only comparison uses that same masked graph and candidate list with the property omitted. The prompt states that case: if no property is supplied, use only the structural context. A use claim needs a shuffle drop and a donor-directed counterfactual flip, scoped to one model and one property. ## Environment Loading and scoring use Python 3.9 or newer and the standard library. ```bash python3 scripts/build_tasks.py python3 scripts/score_tasks.py \ --property dipole \ --condition correct \ --predictions predictions.jsonl ``` `scripts/build_tasks.py` loads every task file and prints the record counts. `scripts/score_tasks.py` compares one prediction file with the label file for that property and view. `--property` is a directory name from the table above. `--condition` is `correct`, `shuffled`, or `counterfactual`. ## Trajectory Score one property and one view at a time. The prediction file is JSONL, one object per line: | Field | Contents | | -------------------------- | ----------------------------------------------------------------------- | | `record_id` | Task id | | `selected_candidate_index` | 0-based index into `candidate_completed_smiles` | | `reasoning` | Justification. The scorer does not read this field. | | `invalid` | `true` when the submission does not parse. Omit the index on that line. | A missing record, a line marked invalid, or an index outside the candidate list counts as incorrect. A duplicate `record_id` is rejected. The scorer prints the hit count, the number of tasks, the accuracy, and the counts of missing, invalid, and out-of-range lines.