Poem Similarity

Start by searching for a poem (by archive ID like “H II 1, 389” or by a word in the text). You’ll see the most similar poems ranked by whichever method you choose.

Side-by-side comparison

The pair buttons (e.g., “TF-IDF vs Jaccard”) show two rankings next to each other — useful for seeing which matches are found by different methods. Poems appearing in both columns are especially reliable matches.

Combined (RRF)

Merges evidence from multiple methods. A poem ranks high only if several algorithms agree. The algorithm badges (T, J, Tr, A) on each card show which methods contributed.

Poem comparison overlay

Click “Compare” on any match to see both poems verse by verse. Highlighted words show what’s shared:

• Yellow — same exact word
• Blue — same root word (different form)
• Purple — same meaning across languages

Curved lines between the poems connect matching verses. Thicker lines = stronger matches.

Network graph & similarity map

A web of connections shows how your poem relates to its matches and their matches. The similarity map plots where matches were collected geographically.

Tips

• Use the score slider to hide weak matches
• Check ET↔FI only (on Translation, Alignment) to see Estonian-Finnish connections
• Click any poem ID to chain-navigate — breadcrumbs track your path
• Deep link: ?poem=H II 1, 389

Verse Similarity

Search for a verse line and see which other verses across the corpus sound similar. Each match is scored by five methods — Jaccard (same words), TF-IDF (same root words), Translation (same meaning across languages), CharBigram (shared letter patterns), and Sentence Embedding (whole-line meaning) — which are then merged into a combined ranking. (See the Overview tab for what each method does.) A separate experimental panel, Semantic neighbours – native embedding, sits below the results and is described at the end of this tab; it is not part of the combined ranking.

Reading a result

Results are a single ranked list, not columns. Each row shows:

• A strip of small coloured squares — one lit square per method that found this match (hover them to see which methods, and at what rank)
• An N/5 count — how many of the five methods agree on this match
• A ×N badge when the same line occurs more than once — identical verses are folded into a single row rather than repeated down the list, and ×N is how many times that exact line appears across the corpus. If several distinct copies (different poems or places) folded into the row, an attestations expander lists each one so you can jump to a specific occurrence.
• A language badge (ET / FI) and the collection place; cross-lingual matches also carry an ET↔FI badge
• Click the arrow to explore onward from that verse — the verse trail tracks where you have been

Sorting the matches

• Best match (default) — balances how many methods agree with how strong each method’s score is, calibrated so no single method dominates. Genuine matches tend to rise to the top, and look-alikes that only one method likes are held back.
• Combined (RRF) — merges the methods purely by the rank each gives a match; a verse ranks high only when several methods rank it high.
• Agreement — orders by the raw number of methods (out of five) that found the match.
• Top raw score — orders by the single strongest method score. Good for surfacing spelling and dialect twins that only the letter-pattern method catches, but it can also float unrelated look-alikes to the top.

Filtering and display

• All / ET↔FI / ET / FI — show all matches, only cross-lingual ones, or only one language
• Place menu — limit to matches from one collection place
• Hide exact repeats — drops the one match that is word-for-word your search line (your search formula re-attested verbatim elsewhere), leaving only the near, non-identical matches. Repeated copies of any other line are already folded into a single ×N row by default (see “Reading a result”), so this control only concerns the search line itself. It greys out when no match is identical to your search line.
• Highlight related words — words spelled identically to one in the search verse are always marked, with no download: the same word repeated within a language, and the same spelling across Estonian and Finnish shown as a likely shared root. Switch this on to also mark the same dictionary word in a different grammatical form (e.g. metsä / metsän) and, across Estonian and Finnish, words that share a root or an English translation; the first time, it loads a one-time word index. It can legitimately find nothing extra to mark when a verse uses dialectal spellings the dictionary does not cover.
• Translations — show an English translation under each verse

Semantic neighbours – native embedding (experimental)

Below the five-method results, an experimental panel finds lines with a similar meaning in any language directly from the original texts, using multilingual sentence-embedding models. It shows two models together, each labelled: LaBSE (Language-agnostic BERT Sentence Embeddings) and mpnet (paraphrase-multilingual-mpnet-base-v2, a Sentence-BERT model), so you can compare them at a glance. It is not part of the combined ranking. Lines that none of the five methods found are highlighted, and the panel opens by itself when it holds such lines.

Each model has its own Show hidden candidates (research view) control that reveals, on click, the stored candidate lines that model’s quality rule rejected, each labelled with the reason it is hidden. Most rejected lines score high on raw similarity yet come from generic phrasings, so read them with caution.

Verse Pairs

Browse the strongest verse-to-verse connections found across the whole corpus — the 50,000 most similar pairs, ranked by combined evidence from shared words, rare words, translations, and letter patterns.

• Sort by any algorithm or use Combined (default)
• Check ET↔FI only to focus on Estonian-Finnish pairs
• Click a pair to see both poems, per-algorithm scores, and a map link
• Switch to By Place Pair to see which collection places share the most verse material
• Select pairs (checkboxes) to expand them on the map — the map then shows where each verse text was collected across the corpus:

Map Expansion (select a pair)

• Main location (large circle) — the place with the most poems containing that verse text
• Spread lines (dashed) — connect the main location to every other place where the same verse appears
• Co-location (purple) — places where both verse texts appear, shown only when such overlap exists
• Green/blue = same-language pairs; gold/pink = cross-lingual pairs

Algorithm badges: J (blue) = Jaccard, T (green) = TF-IDF, Tr (teal) = Translation, C (pink) = CharBigram, S (purple) = Sentence.

By Place Pair view shows identical formulas + near-matches = combined total. Sort by combined count, identical formulas, near-matches, best RRF score, or cross-lingual near-matches.

Counts are a lower bound. Place-pair totals are computed only over the top 50,000 verse pairs, attribute each verse to its primary recorded place, and exclude self-pairs, so true corpus-wide totals are higher. (For scale: 288,635 verses carry no recorded place, and 3,601,619 matching verse pairs were skipped because at least one side had no place.) Cross-lingual (ET↔FI) counts additionally inherit language-labelling caveats for border parishes, so treat them as a lower-bound estimate, not an exact count. Matching also compares normalized text (lowercased, spaces collapsed) and does not fold dialectal spelling variants, so one formula spelled differently across dialects (e.g. peningita vs penningita) is counted as two separate texts rather than one match — a further reason the totals understate true parallelism.

Geography

What this map shows: where the same runosongs turn up in more than one place. Each dot is a place where collectors wrote songs down; each line joins two places that recorded the same or nearly the same verse lines (whole poems in Poem Connections and Combined). A thicker line means more shared material. The data spans four runosong corpora — three Finnish (SKVR, the main archive; KR, published Kalevala-metre poetry; JR, the Ingrian archive) and one Estonian (ERAB). A green same-language line can join places from different Finnish collections; a gold dashed cross-lingual line always joins an Estonian and a Finnish place. Click a dot for the place itself; click a line for what the two places share.

The five views (the buttons above the map):

• Verse Network — every pair of places, compared verse line by verse line. Most links stay within one language (green solid); the rarer Estonian↔Finnish links are gold dashed.
• Estonian↔Finnish Formulas, Poem Connections, Combined — all use the whole corpus, but draw only the connections that cross the Estonian↔Finnish boundary.
• Place Focus — pick one place and see lines to every place it connects to.

Colour key (also shown in the legend below the map). Dots: blue = an Estonian place, orange = a Finnish place (darker shades in the cross-lingual views; an emerald dot marks the place you picked in Place Focus). Lines: Verse Network — green solid = same-language, gold dashed = cross-lingual; Estonian↔Finnish Formulas — purple; Poem Connections — teal; Combined — purple solid = shared verse formulas, teal = shared poems, red dashed = both. In the three cross-lingual views every line is Estonian↔Finnish, so there is just one line colour.

Verse Network

Lines join collection places that recorded matching verse lines anywhere in the corpus. The metric dropdown controls what the thickness measures:

• Normalized surprise — rewards small places that share material relative to their size: five identical lines shared between two tiny collections signals a stronger link than five shared between two huge ones. (Technically: identical shared verse lines ÷ √(each place's distinct verse lines).)
• Combined count (default) — identical shared verse lines plus near-match verse pairs. These are two different units (formula types + near-match instances, like the Verse Pairs tab's Combined), so read it as a strength score, not a clean tally.
• Identical formulas only — how many exact verse lines (formulas — verse lines that recur across the tradition) are recorded in both places, across the whole corpus. This is the count the Normalized-surprise view is built from, before the size correction.
• Near-matches only — how many fuzzy (not identical) verse-pair matches the two places share, across the whole corpus. Each verse keeps its 5 closest matches per method (Jaccard, TF-IDF, translation, char-bigram, sentence-embedding) above a threshold (0.80 within a language, 0.30 across languages). The separate Verse Pairs browser lists only the strongest 50,000 as examples; this count is not limited to them.
• Language filter — All connections / Estonian↔Finnish only / Same-language only.
• Min connections — applies to the count metrics (Combined / Identical / Near-matches), not to the Normalized-surprise ratio. Under Normalized surprise the map shows every pair it can score (at least one shared identical formula and known collection sizes for both places), still limited by Show top.
• Show top (10–500) — keep only the N strongest lines.

Counts are a lower bound. Near-match counts keep only each verse's 5 closest matches per method above the threshold; about 288,000 verses carry no collection place and contribute nothing; each verse is attributed to its primary (first-listed) collection place; self-pairs are excluded; and dialect or orthographic spellings are not folded together, so the same line spelled two ways is at best a near-match, never identical.

Estonian↔Finnish Formulas

Estonian↔Finnish only. A line joins an Estonian and a Finnish place that share cross-lingual verse clusters — groups of near-identical lines that span the language boundary. Dot size and Min clusters reflect each place's total cross-lingual clusters; line thickness and Min connections reflect the clusters this Estonian–Finnish pair shares. The detail panel may also report identical verse-text types shared across the boundary — a different number from the cluster count.

• Language (All / ET / FI), Min clusters, Min connections, Top N sliders
• Show all checkbox — draw every connection instead of the filtered top N

Poem Connections

Estonian↔Finnish only. A line joins places where similar whole poems (not single verses) were collected. The algorithm buttons choose how poems are matched:

• RRF — fuses four poem-level methods (TF-IDF, Jaccard, Translation, Alignment), so a pair ranks high only when several methods agree; the panel shows how many of the four agreed (two or more is more robust).
• Thematic — matches poems through their English translations, so it works across the two languages.
• Semantic — matches poems by overall meaning, using word-embedding similarity on the translations. (Thematic and Semantic are single methods, with no agreement count.)
• Min pairs — hide places sharing fewer than N similar poem pairs; line thickness = number of shared cross-lingual poem pairs.
• Show all checkbox — draw every connection.

Combined

Overlays the verse-formula lines and the poem lines on one map: purple solid = shared verse formulas, teal = shared poems, red dashed = a pair sharing both. Clicking a verse line opens the Estonian↔Finnish Formulas panel; clicking a poem line opens the Poem Connections panel.

• Algorithm (poem matching, as above), Min verse pairs, Min poem pairs sliders
• Show all checkbox (on by default) — toggle the full network vs the filtered view

Place Focus

Pick a single place and see its strongest connections radiating outward.

• Tradition Strength — how much poetic material this place shares with each partner, counted as identical plus near-match verse pairs. Larger, better-collected places tend to score higher.
• Surprising Connections — shared identical verses ÷ the geometric mean of both places' collection sizes, so a small place that shares a lot ranks high.
• Place — type-ahead over 800+ collection places. Language — All / Estonian↔Finnish only / Same-language only. Show — how many of the strongest partner lines to draw (5–60, default 50).
• The emerald dot is the place you picked. Click Focus on this place in any popup to chain-navigate.
• The (ET) / (FI) tag beside each place is a single representative language assigned to that place; language is actually recorded per verse, so a border parish that recorded both Estonian and Finnish verses still shows just one tag. Cross-lingual links are decided by comparing these per-place tags.
• Deep link: ?mode=geography&submode=placefocus&place=Kuusalu

Estonian↔Finnish Song Types panel

In the three cross-lingual views, the collapsible Estonian↔Finnish Song Types panel lists song types that bridge Estonian and Finnish. Expanding it loads a larger dataset, so it may take a moment the first time.

• Min clusters slider, Sort (Score / Clusters / Name), and a New discoveries only checkbox.
• “Confirmed” = the cross-lingual link is already recorded in the project's semantic cross-reference (known to scholars); “new” = an algorithmic candidate not yet cross-referenced.
• Click a song-type name to see its most similar types across the boundary.

Formulaicity

See which parts of a poem are traditional formulas shared across the tradition, and which are found nowhere else in the corpus. Each verse gets a color: dark green = widely shared, yellow = found nowhere else, gray = too short to score.

• Browse Most Formulaic or Most Unique poems, or search by poem ID
• Click any verse in the color strip to see its 5 closest matches from other poems
• The formula-strength index runs 0–100 and rises with three things: how strong a verse's closest parallel is, how many poems echo that line, and how long the line is (short lines match by chance). 80+ marks a widely-shared formula and under 20 a near-unique line; a verse found nowhere else scores 0.

By Formula (clusters)

Switch to By Formula (clusters) at the top to browse the 200 largest groups of recurring verse lines in the tradition — the building blocks singers reused across poems and places. Each cluster shows its member count, the places it reaches, and its Estonian/Finnish split; open one to see sample variants and jump into the Verse Explorer.

Poem Comparison

Compare two runosong poems side-by-side with multi-layer vocabulary highlighting. Words are color-coded by match type:

• Green — same exact wordform in both poems
• Blue — same lemma (dictionary form), different surface form
• Purple — same English translation (cross-lingual match)
• Light blue — unique to Poem A
• Light orange — unique to Poem B

Features

• Verse connections — SVG lines linking similar verses, based on 5 precomputed algorithms
• Algorithm dashboard — 7 poem-level similarity scores (TF-IDF, Jaccard, Translation, Alignment, Semantic, Verse Match, Combined RRF)
• Translations — English translations below each verse
• Formulaicity — Dot indicators showing which verses are traditional formulas
• Mini-map — Click to expand; shows collection locations and distance
• Verse popover — Click any verse to see its closest matches and per-algorithm scores

Keyboard shortcuts

• Ctrl+Shift+S Swap poems
• Ctrl+Shift+C Toggle connections
• Ctrl+Shift+T Toggle translations
• Ctrl+Shift+F Toggle formulaicity
• Ctrl+Shift+1/2/3 Toggle highlight layers
• Ctrl+Shift+R Random pair
• Esc Clear comparison or close popover

Deep link: ?mode=compare&a=SKVR+I1+1.&b=SKVR+I1+2.

Cross-corpus clusters

Each cluster is a group of runosong verses the pipeline judged near-identical — usually the same formula recurring in both traditions. Every cluster holds at least one Estonian-corpus verse (ERAB) and one Finnish-corpus verse (SKVR, KR, JR).

Soft membership. One verse can belong to several clusters, so the cluster sizes add up to more than the distinct-verse total.

Form vs low overlap. The badge marks how much visible word form the two sides share, not whether they match in meaning. Low overlap is an upper bound — mostly cognates whose spelling drifted apart, or short verses just below the line; genuine meaning-only parallels are nearer 1–2%.

KR? flag. Marks a verse whose poem has Estonian text filed under the Finnish KR corpus — a known limitation, so those counts may be slightly inflated.

The search box and the Type, Language-mix, Min-size, and Sort controls filter the list; the count in the header reflects your current filters.

Glossary