Triple
T15371219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dumas family |
E367550
|
entity |
| Predicate | hasLegacyType |
P32463
|
FINISHED |
| Object | literary canon |
—
|
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: literary canon | Statement: [Dumas family, hasLegacyType, literary canon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegacyType Context triple: [Dumas family, hasLegacyType, literary canon]
-
A.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
B.
hasPartInLegacy
chosen
Indicates that an entity includes another entity as a component or constituent specifically within its legacy or historically inherited structure.
-
C.
hasFormerType
Indicates that an entity previously had a certain type or classification that has since changed.
-
D.
hasTypeOfHeritage
Indicates that an entity is associated with a specific category or classification of heritage (such as cultural, natural, or historical heritage).
-
E.
hasLegacyInstitution
Indicates that an entity is historically derived from, or continues the role or traditions of, an earlier institution.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e5c1d548190930bfaf0861595ae |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:18 a.m.