Triple
T3171281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theme from "A Connecticut Yankee" (musical) |
E66350
|
entity |
| Predicate | musicalAdaptationOf |
P1926
|
FINISHED |
| Object | time-travel novel |
—
|
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: time-travel novel | Statement: [Theme from "A Connecticut Yankee" (musical), musicalAdaptationOf, time-travel novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicalAdaptationOf Context triple: [Theme from "A Connecticut Yankee" (musical), musicalAdaptationOf, time-travel novel]
-
A.
notableAdaptation
Indicates that one work is a significant adaptation or reinterpretation of another work.
-
B.
adaptedAs
chosen
Indicates that one work, concept, or entity has been transformed or re-created into another form or medium based on the original.
-
C.
adaptedWorkOf
Indicates that one work is derived from, based on, or reinterprets the content of another pre-existing work.
-
D.
adaptationBy
Indicates a relationship where one entity has been modified, transformed, or reworked by another entity into a new form or version.
-
E.
screenWriterAdaptationBy
Indicates that a person served as the screenwriter responsible for adapting an existing work into a screenplay.
- 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada66c043081908eb23a4fe3420a78 |
completed | March 8, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0076b4819094628f1ad10b8f68 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.