Triple
T11904068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nun's Priest's Tale |
E283228
|
entity |
| Predicate | containsAllusion |
P102154
|
FINISHED |
| Object | classical authorities on dreams |
—
|
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: classical authorities on dreams | Statement: [The Nun's Priest's Tale, containsAllusion, classical authorities on dreams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAllusion Context triple: [The Nun's Priest's Tale, containsAllusion, classical authorities on dreams]
-
A.
hasAllegoricalDepictionsBy
Indicates that one entity is represented through allegorical depictions created by another entity.
-
B.
titleAlludesTo
Indicates that one title makes an indirect or suggestive reference to the content, theme, or another work associated with the other.
-
C.
hasAllegoricalFigures
Indicates that a work, scene, or element includes figures that symbolically represent abstract ideas, concepts, or moral qualities.
-
D.
nameAllusion
Indicates that one entity’s name is derived from, references, or alludes to another entity.
-
E.
allegoricalInterpretation
Indicates that one entity is interpreted as symbolically representing deeper, often moral or spiritual, meanings within another entity (such as a text, image, or event).
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e525460c81909d855048d9c799bf |
completed | April 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:44 p.m.