Triple
T2947608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charybdis |
E79539
|
entity |
| Predicate | transformation |
P28224
|
FINISHED |
| Object | turned into a monster by Zeus |
—
|
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: turned into a monster by Zeus | Statement: [Charybdis, transformation, turned into a monster by Zeus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transformation Context triple: [Charybdis, transformation, turned into a monster by Zeus]
-
A.
transition
Indicates a change of state or condition from one form, phase, or situation to another.
-
B.
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.
-
C.
regionTransformed
Indicates that one region has been changed or converted into another region through some transformation process.
-
D.
movementTransformed
Indicates that an entity’s movement has been altered or converted from one form, state, or pattern into another.
-
E.
transformsUnder
chosen
Indicates a relationship where one entity changes form, state, or structure when subjected to the influence, conditions, or operation specified by another entity.
- 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98b5916c8190b1163bf0b7fa136a |
completed | March 8, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69ad960a70ac8190816b5ae3e8631031 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:57 p.m.