Triple
T8917356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feast of the Seven Fishes |
E212324
|
entity |
| Predicate | courseCompositionRule |
P6730
|
FINISHED |
| Object | no meat from land animals |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: no meat from land animals | Statement: [Feast of the Seven Fishes, courseCompositionRule, no meat from land animals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseCompositionRule Context triple: [Feast of the Seven Fishes, courseCompositionRule, no meat from land animals]
-
A.
compositionRule
chosen
Indicates how multiple elements or components are combined or arranged according to a specific rule or pattern.
-
B.
courseSetting
Indicates the context or environment in which a course is delivered or conducted.
-
C.
courseStructure
Indicates how a course is organized into its constituent parts, such as modules, units, lessons, and their sequencing or hierarchy.
-
D.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
E.
courseShape
Indicates the geometric layout or configuration that defines the path or outline of a course.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca8393b1808190bd4336787ffa2c40 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66120eb08190913ab6c42f26ffb8 |
completed | April 1, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed0ef3c81908cc69eac852ee12a |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:56 p.m.