Triple
T8813778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Die schöne Müllerin |
E209727
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | "Ungeduld" |
E737668
|
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: "Ungeduld" | Statement: [Die schöne Müllerin, hasPart, "Ungeduld"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: "Ungeduld" Context triple: [Die schöne Müllerin, hasPart, "Ungeduld"]
-
A.
Ungeduldig (No. 4)
chosen
Ungeduldig (No. 4) is one of the characterful short piano pieces within Robert Schumann’s Davidsbündlertänze, Op. 6, reflecting his Romantic, introspective style.
-
B.
Hastière
Hastière is a municipality in the Walloon region of southern Belgium, known for its scenic Meuse River setting and historic religious architecture.
-
C.
Hurry
"Hurry" is a song by Teyana Taylor from her 2018 R&B album *K.T.S.E.*.
-
D.
The Long Wait
The Long Wait is a hardboiled crime novel by Mickey Spillane featuring his trademark tough, violent style and twist-driven noir plotting.
-
E.
Agoge
Agoge was the rigorous state-sponsored education and training system in ancient Sparta that prepared male citizens for a life of military service and discipline.
- 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ff02e9c819080a8e45ba9ca044e |
completed | March 31, 2026, 11:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6fb26b148190b66b7138cdf9c97b |
completed | April 3, 2026, 7:43 a.m. |
Created at: March 30, 2026, 6:45 p.m.