Triple
T19950539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Black Watch (Royal Highland Regiment) |
E479541
|
entity |
| Predicate | hasMusicUnit |
P137967
|
FINISHED |
| Object | pipes and drums |
—
|
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: pipes and drums | Statement: [The Black Watch (Royal Highland Regiment), hasMusicUnit, pipes and drums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMusicUnit Context triple: [The Black Watch (Royal Highland Regiment), hasMusicUnit, pipes and drums]
-
A.
hasMusical
Indicates that one entity features, includes, or is associated with a musical work, performance, or musical component.
-
B.
hasMusicCharacteristic
Indicates that an entity possesses a specific musical feature, quality, or attribute.
-
C.
hasMusicCategory
Indicates that something is associated with, classified under, or belongs to a particular category or type of music.
-
D.
hasCommonMusic
Indicates that two entities share at least one piece of music preference, interest, or item in common.
-
E.
hasMusicalSettingsBy
Indicates that a work has been set to music or musically arranged by a specified creator or composer.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a6b694c819080daea9422bcdd38 |
completed | April 20, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:54 p.m.