Triple
T299478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frauenliebe und -leben |
E6166
|
entity |
| Predicate | scoring |
P10576
|
FINISHED |
| Object | voice and piano |
—
|
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: voice and piano | Statement: [Frauenliebe und -leben, scoring, voice and piano]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoring Context triple: [Frauenliebe und -leben, scoring, voice and piano]
-
A.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
B.
marks
Indicates that one entity makes a visible or symbolic sign on, or designates, another entity for identification, emphasis, or distinction.
-
C.
winnerPoints
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
D.
finalScore
Indicates the resulting or overall score achieved after all contributing actions, events, or evaluations are completed.
-
E.
rankingBasis
Indicates the criterion or standard used to determine the order or rank of entities in a ranking.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea0dd1dc8190aecd5afdeb2fd74b |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9398df08190af40063a2de7a1d0 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea07e3bc8190bae593b3264de211 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.