Triple
T7308801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ankia Naat |
E168040
|
entity |
| Predicate | hasMusicalAccompaniment |
P43970
|
FINISHED |
| Object | traditional Assamese instruments |
—
|
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: traditional Assamese instruments | Statement: [Ankia Naat, hasMusicalAccompaniment, traditional Assamese instruments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMusicalAccompaniment Context triple: [Ankia Naat, hasMusicalAccompaniment, traditional Assamese instruments]
-
A.
hasMusical
chosen
Indicates that one entity features, includes, or is associated with a musical work, performance, or musical component.
-
B.
hasMusicalSource
Indicates that something derives from, is based on, or is influenced by a particular musical work or musical material.
-
C.
hasOrchestralFeature
Indicates that something includes, exhibits, or is characterized by a notable orchestral element or component.
-
D.
hasMusicalSettingsBy
Indicates that a work has been set to music or musically arranged by a specified creator or composer.
-
E.
hasMusicalForm
Indicates that one entity (typically a musical work or piece) is characterized by or structured according to a particular musical form.
- 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_69c6888d8e3c81909db79714903baf31 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebda7b748190a230a22ecea79342 |
completed | March 27, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69c6e7705f4881909793071dee50c557 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:01 p.m.