Triple
T18355179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Water (For Charley Patton) |
E439772
|
entity |
| Predicate | hasAllusionType |
P102154
|
FINISHED |
| Object | historical allusion |
—
|
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: historical allusion | Statement: [High Water (For Charley Patton), hasAllusionType, historical allusion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAllusionType Context triple: [High Water (For Charley Patton), hasAllusionType, historical allusion]
-
A.
containsAllusion
chosen
Indicates that one entity includes or incorporates an indirect reference or allusion to another entity.
-
B.
hasAllegoricalDepictionsBy
Indicates that one entity is represented through allegorical depictions created by another entity.
-
C.
nameAllusion
Indicates that one entity’s name is derived from, references, or alludes to another entity.
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
hasAllegoricalFigures
Indicates that a work, scene, or element includes figures that symbolically represent abstract ideas, concepts, or moral qualities.
- 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e516d458148190849ed28fa90eb92b |
completed | April 19, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e44fed3fdc81908f4ed6a81db42416 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:37 a.m.