Triple
T22520177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geistliche Chormusik |
E556751
|
entity |
| Predicate | hasTypeOfTextSetting |
P148701
|
FINISHED |
| Object | through-composed |
—
|
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: through-composed | Statement: [Geistliche Chormusik, hasTypeOfTextSetting, through-composed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfTextSetting Context triple: [Geistliche Chormusik, hasTypeOfTextSetting, through-composed]
-
A.
hasKeyTextType
Indicates that something is associated with a primary or defining type of textual content used as its key or main text.
-
B.
haveMajorTextTypes
Indicates that an entity possesses or is associated with specific primary categories or types of texts.
-
C.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
D.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
E.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
- 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e31f43c8190899f5e35b150fe85 |
completed | April 29, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:50 p.m.