Triple
T37202246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missa brevis in G major |
E922069
|
entity |
| Predicate | usesTextSection |
P161179
|
FINISHED |
| Object | Kyrie eleison |
—
|
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: Kyrie eleison | Statement: [Missa brevis in G major, usesTextSection, Kyrie eleison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTextSection Context triple: [Missa brevis in G major, usesTextSection, Kyrie eleison]
-
A.
usesStringSection
Indicates that one entity employs or incorporates a specific string section (e.g., a substring or string-based component) from another entity in its function or representation.
-
B.
canonicalTextSection
Indicates that one text section is the authoritative or standard version associated with another representation or variant of that section.
-
C.
usesTextBy
Indicates that one entity makes use of or relies on a text authored or provided by another entity.
-
D.
usesTextSetting
Indicates that an entity applies or relies on a particular text configuration, style, or setting in its operation or presentation.
-
E.
useText
chosen
Indicates that one entity employs or applies a specific text as a resource, tool, or content in performing an action or fulfilling a function.
- F. None of above.
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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: May 3, 2026, 4:15 p.m.