Triple
T7001517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rufst du, mein Vaterland |
E162347
|
entity |
| Predicate | hasLyricsIn |
P73517
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Rufst du, mein Vaterland, hasLyricsIn, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLyricsIn Context triple: [Rufst du, mein Vaterland, hasLyricsIn, German]
-
A.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
-
B.
hasExplicitLyrics
Indicates that the referenced content contains explicit language or themes, such as profanity, sexual content, or strong violence.
-
C.
hasLyricCharacter
Indicates that a musical work or song includes a specific character or persona within its lyrics.
-
D.
hasLyricsTheme
Indicates that the lyrics of a work primarily concern or revolve around a specified theme or subject.
-
E.
hasLyricsTone
Indicates the tonal quality or emotional character expressed by the lyrics of a piece of music.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc0f8830819091f4356296234713 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c575f081908b43d95d1d99b1a4 |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:33 p.m.