Anafooride suhtes märgendatud Eesti sõltuvuspuude pank
Bibliographic record
Abstract
Anafooride suhtes märgendatud korpuses on praegu ca 107000 sõna mahus tekste, milles on u 4200 märgendatud asesõna, millest u 3200 on ühendatud oma viitealusega, ülejäänud tuhandel asesõnal viitealus tekstis puudub. Tekstideks on ajalehetekstid ning üks teadustekst (ajakirja Eesti Arst 2004. aasta aastakäik). Märgendatud on järgmised asesõnad kõigis käändevormides ja nende viitealused: isikulised asesõnad (mina/ma, sina/sa, tema/ta, meie/me, teie/te, nemad/nad). Kokku on korpuses 1734 isikulist asesõna, neist 1320 on ühendatud viitealustega. näitav asesõna see esineb korpuses 1489 korral, neist 1084 korral on tal tekstis olemas viitealus. siduvad asesõnad kes ja mis esinevad tekstis kokku 1053 korda, neist 851 juhul on neil olemas viitealus tekstis. Programmid, mis teisendavad puudepanga formaadis faili brati märgendajale sobivaks ja tagasi (pronoomentykeldaja.pl ja brat2inforem) on kataloogis tools. Programmide autorid on Kaili Müürisep ja Katrin Tsepelina.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.219 | 0.048 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".