Triple
T1203709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Circe |
E25838
|
entity |
| Predicate | transformationMethod |
P17711
|
FINISHED |
| Object | magic potions |
—
|
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: magic potions | Statement: [Circe, transformationMethod, magic potions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transformationMethod Context triple: [Circe, transformationMethod, magic potions]
-
A.
transformationProperty
Indicates that one entity has a specific behavior, constraint, or characteristic related to how it changes, converts, or is transformed into another form or state.
-
B.
transformedWith
chosen
Indicates that one entity has been changed, altered, or converted into a different state, form, or representation through the use or application of another specified entity (such as a tool, method, or process).
-
C.
translationMethod
Indicates the technique or process used to translate content from one language or form to another.
-
D.
transformationLocation
Indicates the place or spatial context where a transformation or change of state occurs.
-
E.
decodingMethod
Indicates the technique or process used to convert encoded or encrypted data back into its original, interpretable form.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdbf94188190991f63a84cc76b8a |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.