Triple
T37359579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romanze: Andante |
E927541
|
entity |
| Predicate | hasContrastSection |
P205857
|
FINISHED |
| Object | middle section in minor mode (commonly interpreted) |
—
|
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: middle section in minor mode (commonly interpreted) | Statement: [Romanze: Andante, hasContrastSection, middle section in minor mode (commonly interpreted)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasContrastSection Context triple: [Romanze: Andante, hasContrastSection, middle section in minor mode (commonly interpreted)]
-
A.
hasContrastType
Indicates that one entity is associated with a specific type or category of contrast used to distinguish it from others.
-
B.
hasMainContrast
Indicates a primary opposing or differing relationship between two elements, highlighting the main point of contrast between them.
-
C.
includesContrast
Indicates that one element contains or incorporates a comparison highlighting differences between two or more entities or ideas.
-
D.
hasSectionColor
Indicates that an entity possesses a section (or part) characterized by a specific color.
-
E.
hasNumberOfContrasts
Indicates that an entity is associated with a specific count of distinct contrasts or comparative conditions.
- F. None of above. chosen
Provenance (4 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_69f76eb701788190b40824bc4594d985 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:16 p.m.