Triple
T25215523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Suite in F for Military Band |
E631817
|
entity |
| Predicate | usesFolkTune |
P149801
|
FINISHED |
| Object | Swansea Town |
—
|
NE NERFINISHED |
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: Swansea Town | Statement: [Second Suite in F for Military Band, usesFolkTune, Swansea Town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFolkTune Context triple: [Second Suite in F for Military Band, usesFolkTune, Swansea Town]
-
A.
isFolkSongFrom
Indicates that a folk song originates from or is traditionally associated with a particular place, region, or culture.
-
B.
usesTuneOf
chosen
Indicates that one work is created to be performed with, or is based on, the melody or musical setting originally belonging to another work.
-
C.
hasFolkGenre
Indicates that something belongs to, is categorized under, or is associated with the folk music genre.
-
D.
usesFolkMaterial
Indicates that one entity incorporates or draws upon traditional folk materials, such as melodies, stories, or motifs, in relation to another entity.
-
E.
isOftenSungToTune
Indicates that one song or piece of text is frequently performed using the melody or musical setting of another.
- 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_69e75a8d1aa48190a4320acd3654762c |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f47b8d14c48190a744ce7dd1680150 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 12:59 p.m.