Triple
T12085394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | String Quartets, Op. 33 |
E287792
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Artaria |
E927526
|
NE 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: Artaria | Statement: [String Quartets, Op. 33, publisher, Artaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Artaria Context triple: [String Quartets, Op. 33, publisher, Artaria]
-
A.
Artaria
chosen
Artaria was a prominent Viennese music publishing house known for issuing works by major Classical-era composers such as Mozart and Haydn.
-
B.
Artu
Artu is a diminutive or nickname form of the given name Arturo, commonly used in informal or affectionate contexts.
-
C.
Artés
Artés is a municipality in the comarca of Bages in Catalonia, Spain, known for its wine and cava production.
-
D.
Artsyz
Artsyz is a small town in southwestern Ukraine known for its agricultural surroundings and location within the historical region of Bessarabia.
-
E.
Maderna
Maderna is an Italian surname most notably associated with Bruno Maderna, a prominent 20th-century composer and conductor linked to the postwar avant-garde.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91513bbb0819084a8bb877e03060c |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f666bf1c819089de1235617e775b |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.