Triple
T200151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kubla Khan |
E4085
|
entity |
| Predicate | hasParatext |
P35
|
FINISHED |
| Object | Coleridge’s preface describing an interrupted opium dream |
—
|
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: Coleridge’s preface describing an interrupted opium dream | Statement: [Kubla Khan, hasParatext, Coleridge’s preface describing an interrupted opium dream]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParatext Context triple: [Kubla Khan, hasParatext, Coleridge’s preface describing an interrupted opium dream]
-
A.
hasSacredText
Indicates that an entity possesses or is associated with a particular sacred or religious text.
-
B.
hasPrefaceBy
Indicates that a work includes a preface written by a specified person.
-
C.
hasPart
chosen
Indicates that one entity is a component, segment, or constituent part of another entity.
-
D.
hasCompanionBook
Indicates that one entity (typically a primary work) is associated with another entity that serves as its companion book, providing supplementary or related content.
-
E.
hasLiturgicalReading
Indicates that a religious service, observance, or liturgical event includes or is associated with a specific prescribed reading from scripture or other sacred text.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.