How strongly text supports a specific message or stance (0.0-1.0)
Per-row — runs once for each row.
{{ text }} ALIGNS {{ narrative }}{{ text }} ALIGNS WITH {{ narrative }}| name | type | description |
|---|---|---|
| text | VARCHAR | — |
| narrative | VARCHAR | — |
Infix ALIGNS WITH: filters aligned content
WITH
t AS (
SELECT
'We prioritize safety above all' AS msg
)
SELECT
*
FROM
t
WHERE
msg ALIGNS
WITH
'safety first'Infix ALIGNS: filters aligned content
WITH
t AS (
SELECT
'Our eco-friendly products reduce waste' AS msg
)
SELECT
msg
FROM
t
WHERE
msg ALIGNS 'sustainability' > 0.5Function: low score for misaligned narrative
SELECT
semantic_aligns (
'Cost-cutting is our priority',
'quality and safety first'
)Alias aligns(): detects thematic alignment
SELECT
aligns (
'Innovation drives our strategy',
'forward-thinking'
)Check if an image semantically matches a text query (cross-modal)
Cross-modal cosine similarity between an image and a text query
Fuzzy cross-match two string arrays via bge-m3 embeddings
Checks whether two values match under a relationship
Returns TRUE if text semantically matches the criterion (cross-encoder)
LLM-backed boolean match (escape hatch for MEANS when encoder-based matching is insufficient)
How strongly text supports a specific message or stance (0.0-1.0)
Per-row — runs once for each row.
{{ text }} ALIGNS {{ narrative }}{{ text }} ALIGNS WITH {{ narrative }}| name | type | description |
|---|---|---|
| text | VARCHAR | — |
| narrative | VARCHAR | — |
Infix ALIGNS WITH: filters aligned content
WITH
t AS (
SELECT
'We prioritize safety above all' AS msg
)
SELECT
*
FROM
t
WHERE
msg ALIGNS
WITH
'safety first'Infix ALIGNS: filters aligned content
WITH
t AS (
SELECT
'Our eco-friendly products reduce waste' AS msg
)
SELECT
msg
FROM
t
WHERE
msg ALIGNS 'sustainability' > 0.5Function: low score for misaligned narrative
SELECT
semantic_aligns (
'Cost-cutting is our priority',
'quality and safety first'
)Alias aligns(): detects thematic alignment
SELECT
aligns (
'Innovation drives our strategy',
'forward-thinking'
)Check if an image semantically matches a text query (cross-modal)
Cross-modal cosine similarity between an image and a text query
Fuzzy cross-match two string arrays via bge-m3 embeddings
Checks whether two values match under a relationship
Returns TRUE if text semantically matches the criterion (cross-encoder)
LLM-backed boolean match (escape hatch for MEANS when encoder-based matching is insufficient)