Triple
T8469358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piano Trio in G minor, Op. 17 |
E200241
|
entity |
| Predicate | hasTonality |
P67730
|
FINISHED |
| Object | minor |
—
|
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: minor | Statement: [Piano Trio in G minor, Op. 17, hasTonality, minor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTonality Context triple: [Piano Trio in G minor, Op. 17, hasTonality, minor]
-
A.
contributesToTone
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
B.
tonalCharacteristic
Indicates the specific quality or character of a sound’s tone, such as its color, texture, or expressive nuance, in relation to an entity.
-
C.
isToneNeutral
Indicates that the tone of the referenced content is neither positive nor negative, but emotionally neutral or unbiased.
-
D.
tonal
chosen
Indicates that one entity has a tone, pitch pattern, or tonal quality in relation to another (such as a language, sound, or musical element).
-
E.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
- 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4d5dd088190a79050417f527f14 |
completed | March 31, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_69cbd10072cc819084be1ed9ac7ebe9d |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:11 p.m.