Add source: sejm_interpellations (10th-term written Q&A)

Ship the current-term interpellations and HTML ministry replies as a
written-register complement to sejm_api speeches. Term 9 was empty on
the API; 7–8 were skipped because PPC already covers them.

Co-authored-by: Cursor <cursoragent@cursor.com>

CHANGELOG.md

@@ -1,5 +1,20 @@
 # Changelog
 
+## v0.2.6 (2026-09-05)
+
+- Added `sejm_interpellations` (Paweł Puzio / `ppuzio`): 25,950 documents /
+  28,180,895 cl100k-proxy tokens of 10th-term Sejm interpellations, written
+  questions, and HTML ministry replies (2023-11-15 – 2026-09-03). Same legal
+  basis as `sejm_api` (art. 4 pkt 2 pr. aut. + Open Data Act). Spoken floor
+  speeches are not included.
+- Fetch: `src/fetch_sejm_interpellations.py` (HTML `/body` only; header chrome
+  stripped into meta; PDF-only and keyless replies skipped; `scrub_pii` from
+  #20). Term 9 listed empty on the API. Build dropped 553 exact-duplicate
+  texts (26,503 → 25,950). Every row has a signatory/minister `author`.
+- README source table now also lists already-merged `sejm_api` and
+  `wiktionary_examples` so the card totals match the per-source `stats.json`
+  files: 4,392,601 documents / 9,704,694,875 tokens across 21 sources.
+
 ## v0.2.5 (2026-08-14)
 
 - Added the community contribution `samorzad_gov_pl` by Dawid Majewski

README.md

@@ -19,13 +19,13 @@ A continuously developed, **openly-licensed**, human-text Polish corpus — a Po
 edition in the [Dynaword](https://huggingface.co/datasets/danish-foundation-models/danish-dynaword)
 family (Enevoldsen et al., [arXiv:2508.02271](https://arxiv.org/abs/2508.02271)).
 
-> **v0.2.5 stable** · 4,319,200 documents · **9.64B tokens**
-> (tiktoken proxy; canonical Llama-3 count at release) · 18 sources
-> Updated: **2026-08-14**
+> **v0.2.6 stable** · 4,392,601 documents · **9.70B tokens**
+> (tiktoken proxy; canonical Llama-3 count at release) · 21 sources
+> Updated: **2026-09-05**
 
 > **v0.3-dev experimental track** · quality/diversity workflow, source-gate
 > validation and candidate-data audits. This is development work, not a released
-> corpus version, and it does not replace the v0.2.5 stable parquets.
+> corpus version, and it does not replace the v0.2.6 stable parquets.
 
 > **Europeana validation artifact (2026-07-10)** · a separate reproducible
 > 810-document direct-ingestion sample stored under the legacy path
@@ -37,7 +37,8 @@ family (Enevoldsen et al., [arXiv:2508.02271](https://arxiv.org/abs/2508.02271))
 
 | version | status | documents | tokens | notes |
 |---|---|---:|---:|---|
-| `v0.2.5` | stable release | 4,319,200 | 9.64B | Adds community-contributed `samorzad_gov_pl` with institution-level author attribution and a URL-bearing attribution sidecar. |
+| `v0.2.6` | stable release | 4,392,601 | 9.70B | Adds `sejm_interpellations` (10th-term written Q&A). README source table now also lists already-merged `sejm_api` and `wiktionary_examples` so totals match `stats.json`. |
+| `v0.2.5` | previous stable | 4,319,200 | 9.64B | Adds community-contributed `samorzad_gov_pl` with institution-level author attribution and a URL-bearing attribution sidecar. |
 | `v0.2.4` | previous stable | 4,246,429 | 9.60B | Expanded `european_hplt_v3_pl` to WDS bins 10-5 (+1.49M docs / 2.04B tok); phone PII-scrub hardening (independent dual-lens) + cross-source dedup (zero-overlap). |
 | `v0.2.3` | previous stable | 2,710,974 | 6.88B | Adds community-contributed `european_hplt_v3_pl`, `global_voices` and `nkjp1m`. |
 | `v0.2.2` | previous stable | 2,579,963 | 6.36B | Added community-contributed `govpl`: 88,190 docs / 80.7M tokens. |
@@ -55,7 +56,16 @@ family (Enevoldsen et al., [arXiv:2508.02271](https://arxiv.org/abs/2508.02271))
 
 ### Version details
 
-#### v0.2.5 — current stable
+#### v0.2.6 — current stable
+
+Added `sejm_interpellations`: **25,950 documents / 28,180,895 cl100k-proxy
+tokens** of 10th-term Sejm interpellations, written questions, and HTML
+ministry replies. Same API and kadencja as `sejm_api`, written register
+rather than floor speeches. PDF-only replies skipped; term 9 listed empty on
+the API at fetch time. Header chrome stripped at fetch; `scrub_pii` already
+on `main` (#20) ran before jsonl write.
+
+#### v0.2.5 — previous stable
 
 Added `samorzad_gov_pl`: **72,771 documents / 41,154,506 cl100k-proxy
 tokens** from 246 Polish local public institutions and one central platform
@@ -145,7 +155,7 @@ as the redistributing aggregator; this release does not claim ownership of them
 |---|---|---|
 | [Kacper Wikieł](https://huggingface.co/kacperwikiel) | Project maintainer; corpus curation, source and license review, release engineering, documentation, validation and reproducible build workflow. | all releases |
 | [Bart Kobyliński](https://huggingface.co/bartoszkobylinski1) | Added `1000_novels`; expanded Biblioteka Nauki and Europeana ingestion with per-document license and author metadata. | `v0.2.1`, [PR #1](https://huggingface.co/datasets/SlayerLab/polish-dynaword/discussions/1) |
-| [Paweł Puzio](https://huggingface.co/ppuzio) | Built `govpl`: subsite discovery, direct ingestion pipeline, dataset artifact, contract tests and documentation. | `v0.2.2`, [PR #9](https://huggingface.co/datasets/SlayerLab/polish-dynaword/discussions/9) |
+| [Paweł Puzio](https://huggingface.co/ppuzio) | Built `govpl`; built `sejm_interpellations` (10th-term written Q&A + HTML replies). | `v0.2.2`, [PR #9](https://huggingface.co/datasets/SlayerLab/polish-dynaword/discussions/9); `v0.2.6` |
 | [Arkadiusz Słota](https://huggingface.co/Maggio33) | Built & expanded `european_hplt_v3_pl`: HPLT v3 WDS 10+9 (PR #5) then WDS 10-5 expansion (+1,493,384 docs / 2.04B tok), modular cleaning pipeline, phone-recall PII-scrub (v12b, independent dual-lens), cross-source dedup-vs-base (zero-overlap), validation and documentation. | `v0.2.3` (PR #5), `v0.2.4` |
 | [Dawid Majewski](https://huggingface.co/dawidmajewski) | Added the reviewed Global Voices Polish corpus; built `samorzad_gov_pl` with direct acquisition, institution attribution, licensing evidence, release artifact and reproducible conversion. | `v0.2.3`, [PR #7](https://huggingface.co/datasets/SlayerLab/polish-dynaword/discussions/7); `v0.2.5` |
 | [1am](https://huggingface.co/1am) | Added `nkjp1m`: the manually annotated 1-million-word NKJP subcorpus, direct fetch/build pipeline, source documentation and release artifact. | `v0.2.3`, [PR #8](https://huggingface.co/datasets/SlayerLab/polish-dynaword/discussions/8) |
@@ -175,14 +185,17 @@ files is not listed as a data contribution.
 | [govpl](data/govpl/govpl.md) | gov.pl — Polish government press releases | `CC-BY-SA-4.0` | 88,190 | 80.7M |
 | [1000_novels](data/1000_novels/1000_novels.md) | 1000 Novels Corpus (CLARIN-PL) | `CC-BY-4.0` | 1,000 | 60.5M |
 | [samorzad_gov_pl](data/samorzad_gov_pl/samorzad_gov_pl.md) | samorzad.gov.pl — Polish public-sector institutions | `CC-BY-SA-4.0` | 72,771 | 41.2M |
+| [sejm_api](data/sejm_api/sejm_api.md) | Sejm API parliamentary speeches (2023 onward) | `public-domain (official documents)` | 38,812 | 36.3M |
 | [wikiquote](data/wikiquote/wikiquote.md) | Polish Wikiquote (quotations) | `CC-BY-SA-3.0` | 30,363 | 31.9M |
+| [sejm_interpellations](data/sejm_interpellations/sejm_interpellations.md) | Sejm interpellations and written questions (10th term) | `public-domain (official documents)` | 25,950 | 28.2M |
 | [eltec_pol](data/eltec_pol/eltec_pol.md) | ELTeC-pol (European Literary Text Collection, Polish) | `CC-BY-4.0` | 100 | 21.5M |
 | [wikivoyage](data/wikivoyage/wikivoyage.md) | Polish Wikivoyage (travel guides) | `CC-BY-SA-3.0` | 13,645 | 17.1M |
 | [wikibooks](data/wikibooks/wikibooks.md) | Polish Wikibooks (open textbooks) | `CC-BY-SA-3.0` | 9,112 | 15.6M |
 | [wikinews](data/wikinews/wikinews.md) | Polish Wikinews | `CC-BY-2.5` | 24,386 | 12.1M |
 | [global_voices](data/global_voices/global_voices.md) | Global Voices Polish | `CC-BY-3.0` | 2,040 | 3.7M |
 | [nkjp1m](data/nkjp1m/nkjp1m.md) | The manually annotated 1-million word subcorpus of the National Corpus of Polish | `CC-BY` | 18,381 | 2.6M |
-| **total** | | | **4,246,429** | **9,597.9M** |
+| [wiktionary_examples](data/wiktionary_examples/wiktionary_examples.md) | Polish Wiktionary usage examples | `CC-BY-SA-3.0` | 8,639 | 1.1M |
+| **total** | | | **4,392,601** | **9,704.7M** |
 
 ## Method
 Only **human-authored** text — no synthetic, machine-translated, or auto-transcribed

artifacts/source_findings.md

@@ -680,11 +680,11 @@ designing a gate on one — two of the four were empty in every row sampled.
 
 ## Sejm API — interpelacje i zapytania poselskie (recheck)
 
-**Investigated:** 2026-08-31
-**Verdict:** `ready to build` — supersedes the 2026-08-27 `hold — recheck` above.
-The host was reachable, every endpoint in question exists, and the reply bodies
-are retrievable as HTML for about half the replies. **~115M words ≈ 305M tokens**
-with no new license work.
+**Investigated:** 2026-08-31; built 2026-09-05
+**Verdict:** `added` (term 10 only, this PR) — supersedes the 2026-08-27
+`hold — recheck` above. The 305M estimate was terms 7–10 HTML. Term 9 listed
+`X-Total-Count: 0` at fetch time; 7–8 were not fetched (PPC already has
+interpellations through 2019). Shipped shard: **25,950 docs / 28,180,895 tok**.
 
 ### Enumeration — solved
 

data/sejm_interpellations/sejm_interpellations.md

@@ -0,0 +1,108 @@
+# sejm_interpellations
+
+Interpelacje i zapytania pisemne z 10. kadencji Sejmu, wraz z odpowiedziami
+ministerstw dostępnymi jako HTML.
+
+## Dataset description
+
+- **Source (upstream):** https://api.sejm.gov.pl/
+- **Source documentation:** https://api.sejm.gov.pl/sejm.html
+- **Domain:** political/written
+- **Language:** Polish (`pl`)
+- **License:** `public-domain (official documents)`
+- **Created (range):** 2023-11-15, 2026-09-03
+- **Added:** 2026-09-05
+- **OCR:** no
+
+## Licensing — traceable basis
+
+Official parliamentary materials are excluded from copyright under Polish
+Copyright Act art. 4 pkt 2
+(https://eli.gov.pl/api/acts/DU/2025/24/text/O/D20250024.pdf). Reuse of
+public-sector information is governed by the Polish Open Data Act arts. 2(12),
+5, 14 and 17 (https://eli.gov.pl/api/acts/DU/2023/1524/text.html). Same basis
+as the shipped `sejm_api` shard. No Creative Commons grant is asserted.
+
+## What the texts are
+
+Written questions from MPs to ministers (`interpellations`,
+`writtenQuestions`) and the ministry replies that the API serves as HTML.
+Spoken floor speeches are **not** included — those are `sejm_api` (2023–) and
+[#18](https://huggingface.co/datasets/SlayerLab/polish-dynaword/discussions/18)
+(2011–2022). Same kadencja, different genre.
+
+PDF-only replies (`onlyAttachment: true`) and keyless prolongation stubs are
+skipped. Term 9 listed `X-Total-Count: 0` on both collections at fetch time
+and is not in this shard. Terms 7–8 were not fetched (PPC already covers
+interpellations through 2019).
+
+## Provenance and reproducibility
+
+```bash
+python3 src/fetch_sejm_interpellations.py --out ~/speakleash --terms 9,10 --workers 4
+python3 src/build_dynaword.py --sources sejm_interpellations --speakleash-dir ~/speakleash --out .
+```
+
+`src/fetch_sejm_interpellations.py` pulls HTML `/body` endpoints, strips
+header chrome (nr / recipient / title / signatory / date) into `meta`, then
+runs `src/scrub_pii.py` (phones → `[Telefon]`; email / PESEL / NIP / REGON /
+IBAN → `[PII]`). Names of public officials stay. `build_dynaword.py` applies
+the usual gates (strip, `< 200` chars, Polish diacritic ratio, exact sha1).
+
+## Why include it
+
+The corpus already has spoken Sejm (`parliamentary`, `sejm_api`). This adds
+the written Q&A register for the current term: longer, formal, ministry-voiced
+replies that do not appear in the speech shards.
+
+## Statistics
+
+| Measure | Value |
+|---|---:|
+| JSONL rows read | 26,503 |
+| Exact duplicate texts removed | 553 |
+| Documents published | 25,950 |
+| Characters | 78,607,831 |
+| Tokens (`cl100k_base` proxy) | 28,180,895 |
+| Documents with author attribution | 25,950 |
+
+JSONL mix before dedup: 19,413 interpellations, 3,889 written questions,
+2,730 interpellation replies, 471 written-question replies. All term 10.
+
+## Filters applied (build_dynaword.py)
+
+- drop documents < 200 chars: **0**
+- drop non-Polish (diacritic ratio): **0**
+- exact sha1 dedup: **553**
+- OCR alpha-ratio: **0**
+- read 26,503 → kept 25,950
+
+## Sample
+
+Question (author `Daniel Milewski`):
+
+```
+Szanowny Panie Ministrze,
+
+latem 2022 roku na podlaskiej części granicy z Białorusią ukończono zaporę
+fizyczną, czyli 5,5-metrowy płot ze stalowych przęseł zwieńczony drutem
+żyletkowym. Ogrodzenie stoi na 186 kilometrach. […]
+```
+
+Reply (author `sekretarz stanu w Ministerstwie Spraw Zagranicznych
+Władysław Teofil Bartoszewski`):
+
+```
+Szanowny Panie Marszałku,
+
+w odpowiedzi na zapytanie poselskie nr 3472 pana posła Bronisława Foltyna
+w sprawie Instytutu Polskiego w Szwajcarii, uprzejmie informuję, co
+następuje. […]
+```
+
+## Privacy and limitations
+
+Regex PII scrub at fetch time is not a guarantee of zero personal data.
+Constituency casework in interpellations can name private persons; those
+names are left in (officials acting in capacity are not treated as PII).
+Downstream users must review applicable privacy and source terms.

data/sejm_interpellations/sejm_interpellations.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a309b9300933ee772d3c8fcda7546461cbf072807ea37939b6101fc2eb33bead
+size 27168758

data/sejm_interpellations/sejm_interpellations.stats.json

@@ -0,0 +1,16 @@
+{
+  "read": 26503,
+  "kept": 25950,
+  "drop_short": 0,
+  "drop_lang": 0,
+  "drop_dup": 553,
+  "drop_ocr": 0,
+  "chars": 78607831,
+  "tokens": 28180895,
+  "licenses": {
+    "public-domain (official documents)": 25950
+  },
+  "authors_with_value": 25950,
+  "secs": 1.8,
+  "license": "public-domain (official documents)"
+}

src/build_dynaword.py

@@ -65,6 +65,12 @@ def _meta_value(row: dict, keys: tuple[str, ...], default: str = "") -> str:
         value = _first_text(row.get(key))
         if value:
             return value
+    nested = row.get("meta")
+    if isinstance(nested, dict):
+        for key in keys:
+            value = _first_text(nested.get(key))
+            if value:
+                return value
     return default
 
 

src/fetch_sejm_interpellations.py

@@ -11,10 +11,12 @@ lives in meta, not text. PII regex-scrub runs before the line is written.
 
 Usage:
   python3 src/fetch_sejm_interpellations.py --out ~/speakleash
+  python3 src/fetch_sejm_interpellations.py --out ~/speakleash --terms 10 --workers 4
   python3 src/fetch_sejm_interpellations.py --out ~/speakleash --terms 10 --max-docs 30
 """
 from __future__ import annotations
 import argparse, json, re, subprocess, sys, time
+from concurrent.futures import ThreadPoolExecutor, wait, FIRST_COMPLETED
 from pathlib import Path
 from urllib.error import HTTPError, URLError
 from urllib.request import Request, urlopen
@@ -153,6 +155,24 @@ def iter_listing(term, collection, page_size):
             return
 
 
+def _jobs_for_item(item):
+    jobs = [(False, None)]
+    for reply in item.get("replies") or []:
+        if should_fetch_reply(reply):
+            jobs.append((True, reply))
+    return jobs
+
+
+def _fetch_job(term, collection, item, reply):
+    url = body_url(term, collection, item.get("num"), reply)
+    raw, hdrs = _get(url)
+    if raw is None:
+        return url, None, hdrs.get("error")
+    kind = _KIND[(collection, bool(reply))]
+    rec = normalize_document(kind, item, raw.decode("utf-8", "replace"), reply)
+    return url, rec, None
+
+
 def main(argv=None) -> int:
     ap = argparse.ArgumentParser()
     ap.add_argument("--out", default="~/speakleash")
@@ -160,8 +180,11 @@ def main(argv=None) -> int:
                     help="comma-separated Sejm terms (default 7-10)")
     ap.add_argument("--collections", default="interpellations,writtenQuestions")
     ap.add_argument("--page-size", type=int, default=50)
+    ap.add_argument("--workers", type=int, default=4,
+                    help="parallel body fetches (default 4)")
     ap.add_argument("--max-docs", type=int, default=0, help="stop after N kept rows")
     args = ap.parse_args(argv)
+    workers = max(1, args.workers)
 
     terms = [int(t) for t in args.terms.split(",") if t.strip()]
     collections = [c.strip() for c in args.collections.split(",") if c.strip()]
@@ -178,49 +201,76 @@ def main(argv=None) -> int:
                 pass
         print(f"resume: {len(done):,} already fetched")
 
-    kept = seen = skipped = 0
+    kept = seen = skipped = finished = 0
     t0 = time.time()
-    with jsonl.open("a", encoding="utf-8") as fo:
+    stop = False
+
+    def consume(fut, fo):
+        nonlocal kept, skipped, finished
+        url, rec, err = fut.result()
+        done.add(url)
+        finished += 1
+        if err:
+            skipped += 1
+            print(f"  WARN skip {url} {err}", file=sys.stderr, flush=True)
+        elif rec:
+            fo.write(json.dumps(rec, ensure_ascii=False) + "\n")
+            fo.flush()
+            kept += 1
+        else:
+            skipped += 1
+        if finished % 200 == 0:
+            print(f"  seen {seen:,} kept {kept:,} skip {skipped:,} "
+                  f"{finished / max(time.time() - t0, 1):.1f}/s", flush=True)
+
+    with jsonl.open("a", encoding="utf-8") as fo, \
+            ThreadPoolExecutor(max_workers=workers) as pool:
+        pending = set()
+        limit = max(workers * 4, workers)
+
+        def drain(block=False):
+            nonlocal pending
+            if not pending:
+                return
+            if block:
+                finished = pending
+                wait(finished)
+            else:
+                finished, pending = wait(pending, return_when=FIRST_COMPLETED)
+            for fut in finished:
+                if not block:
+                    pending.discard(fut)
+                consume(fut, fo)
+            if block:
+                pending = set()
+
+        print(f"workers={workers}", flush=True)
         for term in terms:
+            if stop:
+                break
             for collection in collections:
+                if stop:
+                    break
                 print(f"term {term} {collection}", flush=True)
                 for item in iter_listing(term, collection, args.page_size):
-                    jobs = [(False, None)]
-                    for reply in item.get("replies") or []:
-                        if should_fetch_reply(reply):
-                            jobs.append((True, reply))
-                    for is_reply, reply in jobs:
+                    if stop:
+                        break
+                    for is_reply, reply in _jobs_for_item(item):
                         url = body_url(term, collection, item.get("num"), reply)
                         seen += 1
                         if url in done:
                             continue
-                        raw, hdrs = _get(url)
-                        if raw is None:
-                            skipped += 1
-                            print(f"  WARN skip {url} {hdrs.get('error')}",
-                                  file=sys.stderr, flush=True)
-                            continue
-                        kind = _KIND[(collection, is_reply)]
-                        rec = normalize_document(
-                            kind, item, raw.decode("utf-8", "replace"), reply
-                        )
-                        done.add(url)
-                        if rec:
-                            fo.write(json.dumps(rec, ensure_ascii=False) + "\n")
-                            kept += 1
-                        else:
-                            skipped += 1
-                        if seen % 200 == 0:
-                            print(f"  seen {seen:,} kept {kept:,} skip {skipped:,} "
-                                  f"{seen / max(time.time() - t0, 1):.1f}/s", flush=True)
+                        pending.add(pool.submit(
+                            _fetch_job, term, collection, item, reply,
+                        ))
+                        if len(pending) >= limit:
+                            drain()
                         if args.max_docs and kept >= args.max_docs:
+                            stop = True
                             break
-                    if args.max_docs and kept >= args.max_docs:
+                    if stop:
                         break
-                if args.max_docs and kept >= args.max_docs:
-                    break
-            if args.max_docs and kept >= args.max_docs:
-                break
+        drain(block=True)
 
     print(f"fetched {kept:,} new docs ({skipped:,} skipped); compressing...", flush=True)
     subprocess.run(

src/make_docs.py

@@ -13,8 +13,8 @@ sys.path.insert(0, str(Path(__file__).resolve().parent))
 from sources import SOURCES, EXCLUDED, ADDED
 
 ROOT = Path(__file__).resolve().parent.parent
-VERSION = "0.2.5"
-RELEASE_DATE = "2026-08-14"
+VERSION = "0.2.6"
+RELEASE_DATE = "2026-09-05"
 CONTACT = "k.wikiel@gmail.com"  # notice-and-takedown / data-removal requests
 
 # Dupochron: documented good-faith provenance + no-warranty + takedown + PII.

src/sources.py

@@ -101,7 +101,7 @@ SOURCES = {
     },
     "sejm_interpellations": {
         "file_key": "sejm_interpellations",
-        "pretty": "Sejm interpellations and written questions (terms 7–10)",
+        "pretty": "Sejm interpellations and written questions (10th term)",
         "license": "public-domain (official documents)",
         "license_spdx": "LicenseRef-Polish-Official-Documents",
         "traceable": "Official parliamentary materials excluded from copyright "
@@ -110,11 +110,12 @@ SOURCES = {
         "upstream": "https://api.sejm.gov.pl/",
         "provenance": "Fetched from api.sejm.gov.pl HTML body endpoints by "
                       "src/fetch_sejm_interpellations.py (interpellations + "
-                      "writtenQuestions, terms 7–10). Header chrome stripped into "
-                      "meta; attachment-only and keyless replies skipped; "
+                      "writtenQuestions, term 10). Term 9 listed empty on the "
+                      "API at fetch time. Header chrome stripped into meta; "
+                      "attachment-only and keyless replies skipped; "
                       "src/scrub_pii.py applied before jsonl write.",
         "domain": "political/written",
-        "created": "2011-11-08, 2026-09-04",
+        "created": "2023-11-15, 2026-09-03",
         "is_ocr": False,
         "custom_datasheet": True,
     },

src/test_sejm_interpellations_contract.py

@@ -1,12 +1,19 @@
 """TDD contract for Sejm interpellations / written-questions ingestion."""
+import json
 import sys
 import unittest
 from pathlib import Path
 
 sys.path.insert(0, str(Path(__file__).resolve().parent))
 
+ROOT = Path(__file__).resolve().parent.parent
+PARQUET = ROOT / "data" / "sejm_interpellations" / "sejm_interpellations.parquet"
+STATS = ROOT / "data" / "sejm_interpellations" / "sejm_interpellations.stats.json"
+CANON = ["id", "text", "source", "added", "created", "token_count", "license", "author"]
+
 from fetch_sejm_interpellations import (
     MIN_CHARS,
+    _jobs_for_item,
     normalize_document,
     should_fetch_reply,
 )
@@ -115,6 +122,48 @@ class SejmInterpellationsContractTest(unittest.TestCase):
         self.assertTrue(row["meta"]["url"].endswith("/writtenQuestions/1/body"))
         self.assertEqual(row["meta"]["kind"], "written_question")
 
+    def test_jobs_include_html_replies_only(self):
+        item = {
+            **ITEM,
+            "replies": [
+                {"key": "KEEP", "onlyAttachment": False},
+                {"key": "PDF", "onlyAttachment": True},
+                {"onlyAttachment": False},
+            ],
+        }
+        jobs = _jobs_for_item(item)
+        self.assertEqual(jobs[0], (False, None))
+        self.assertEqual(len(jobs), 2)
+        self.assertEqual(jobs[1][1]["key"], "KEEP")
+
+
+class SejmInterpellationsParquetTest(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        if not PARQUET.is_file():
+            raise unittest.SkipTest("parquet not built yet")
+        import pyarrow.parquet as pq
+        cls.tbl = pq.read_table(PARQUET)
+        cls.stats = json.loads(STATS.read_text(encoding="utf-8"))
+
+    def test_canonical_schema_and_uniform_source_license(self):
+        self.assertEqual(self.tbl.column_names, CANON)
+        src = set(self.tbl["source"].to_pylist())
+        lic = set(self.tbl["license"].to_pylist())
+        self.assertEqual(src, {"sejm_interpellations"})
+        self.assertEqual(lic, {"public-domain (official documents)"})
+
+    def test_nonempty_text_and_positive_tokens(self):
+        texts = self.tbl["text"].to_pylist()
+        toks = self.tbl["token_count"].to_pylist()
+        self.assertTrue(all(t and t.strip() for t in texts))
+        self.assertTrue(all(n > 0 for n in toks))
+
+    def test_stats_match_parquet(self):
+        self.assertEqual(self.stats["kept"], self.tbl.num_rows)
+        self.assertEqual(self.stats["tokens"], sum(self.tbl["token_count"].to_pylist()))
+        self.assertEqual(self.stats["authors_with_value"], self.tbl.num_rows)
+
 
 if __name__ == "__main__":
     unittest.main()