Triple
T31434308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MWV Q 10 |
E801882
|
entity |
| Predicate | hasCategoryDescription |
P11875
|
FINISHED |
| Object | chamber music with violin |
—
|
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: chamber music with violin | Statement: [MWV Q 10, hasCategoryDescription, chamber music with violin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCategoryDescription Context triple: [MWV Q 10, hasCategoryDescription, chamber music with violin]
-
A.
hasDescription
chosen
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
B.
hasCategories
Indicates that an entity is associated with one or more categories that classify or group it.
-
C.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
D.
hasCategorySystem
Indicates that an entity is associated with or organized according to a particular categorization system.
-
E.
hasCategoryCount
Indicates the number of distinct categories associated with a given entity.
- 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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: April 30, 2026, 9 p.m.