Triple
T34157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Stafford Smith |
E679
|
entity |
| Predicate | hasPartInDiscography |
P1995
|
FINISHED |
| Object | English cathedral music repertoire |
—
|
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: English cathedral music repertoire | Statement: [John Stafford Smith, hasPartInDiscography, English cathedral music repertoire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInDiscography Context triple: [John Stafford Smith, hasPartInDiscography, English cathedral music repertoire]
-
A.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
B.
hasNotableRecordingBy
Indicates that an entity (such as a work or composition) has a well-known or significant recording created or performed by a specified agent (such as an artist, ensemble, or label).
-
C.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
D.
reliesOnInstrument
Indicates that an action or process depends on or is carried out using a particular instrument or tool.
-
E.
hasChorus
Indicates that something (typically a song or musical piece) includes a chorus section as part of its structure.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a24872e4e481908567850168d65015 |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a248fef2b881908180bd4e32e58cb5 |
completed | Feb. 28, 2026, 1:46 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.