Triple
T37922252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biamonti 247 |
E945994
|
entity |
| Predicate | thematicIndexForComposer |
P166598
|
FINISHED |
| Object | Ludwig van Beethoven |
—
|
NE NERFINISHED |
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: Ludwig van Beethoven | Statement: [Biamonti 247, thematicIndexForComposer, Ludwig van Beethoven]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thematicIndexForComposer Context triple: [Biamonti 247, thematicIndexForComposer, Ludwig van Beethoven]
-
A.
hasComposerOfTheme
Indicates that an entity serves as the composer responsible for creating the musical theme associated with another entity.
-
B.
notableComposerOfType
Indicates that an entity is a well-known or distinguished composer associated with a specified type, category, or genre of composition.
-
C.
associatedComposerPosition
Indicates that there is a specific role, title, or position held by a composer in relation to a given context or entity.
-
D.
focusesOnComposer
chosen
Indicates that something (such as a work, study, or discussion) is primarily concerned with or centered around a particular composer.
-
E.
composerOfThemeMusic
Indicates that one entity is the person who composed the theme music associated with another entity (such as a show, film, or series).
- 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.