Triple
T1963274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddenbrooks |
E42632
|
entity |
| Predicate | inCanon |
P977
|
FINISHED |
| Object | 20th-century literary classics |
—
|
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: 20th-century literary classics | Statement: [Buddenbrooks, inCanon, 20th-century literary classics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inCanon Context triple: [Buddenbrooks, inCanon, 20th-century literary classics]
-
A.
usesCanon
Indicates that one entity employs or relies on another entity as its standard, reference, or authoritative source.
-
B.
inCanonOf
chosen
Indicates that one entity is officially recognized as part of the established canon or authoritative body of works associated with another entity.
-
C.
givesCanon
Indicates that one entity provides or establishes an official or authoritative version (canon) of something for another entity or context.
-
D.
usesCanons
Indicates that one entity employs or makes use of canons (such as rules, principles, or artillery pieces) in relation to another entity or context.
-
E.
typeOfCanonry
Indicates that one canonry is classified as a specific kind or category of canonry in relation to another.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.