Triple
T223729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Storm on the Sea of Galilee |
E4270
|
entity |
| Predicate | compositionFeature |
P5048
|
FINISHED |
| Object | diagonal composition |
—
|
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: diagonal composition | Statement: [The Storm on the Sea of Galilee, compositionFeature, diagonal composition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compositionFeature Context triple: [The Storm on the Sea of Galilee, compositionFeature, diagonal composition]
-
A.
compositionRule
Indicates how multiple elements or components are combined or arranged according to a specific rule or pattern.
-
B.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
C.
componentType
Indicates that one entity specifies or classifies the kind or category of component that another entity represents or uses.
-
D.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
E.
featureType
chosen
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dec53ac8190912f3d79576131fa |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b5739dc8190bad8bfa330ce0499 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.