Triple
T11983266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiana |
E285210
|
entity |
| Predicate | temporarilyTransformedInto |
P65473
|
FINISHED |
| Object | frog |
—
|
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: frog | Statement: [Tiana, temporarilyTransformedInto, frog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporarilyTransformedInto Context triple: [Tiana, temporarilyTransformedInto, frog]
-
A.
transformedDuring
Indicates that an entity undergoes a change in form, state, or structure within the duration of a specified event or process.
-
B.
bodyTransformedInto
chosen
Indicates that one entity’s physical form is changed or converted into another specified form or entity.
-
C.
wasTransformedBy
Indicates that an entity has undergone a change of state, form, or condition as the result of an action, process, or agent.
-
D.
usesTransformation
Indicates that one entity applies or relies on a specific transformation process, method, or function to operate on or convert another entity.
-
E.
transformedWith
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).
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903acbb9081908fe7f8360057785c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.