Triple
T34949230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hanks as adult Josh Baskin |
E1007941
|
entity |
| Predicate | magicallyTransformedFrom |
P85351
|
FINISHED |
| Object | young Josh Baskin |
—
|
NE NERFINISHED |
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: young Josh Baskin | Statement: [Tom Hanks as adult Josh Baskin, magicallyTransformedFrom, young Josh Baskin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: magicallyTransformedFrom Context triple: [Tom Hanks as adult Josh Baskin, magicallyTransformedFrom, young Josh Baskin]
-
A.
wasTransformedBy
chosen
Indicates that an entity has undergone a change of state, form, or condition as the result of an action, process, or agent.
-
B.
transformedIn
Indicates that one entity has been changed, converted, or altered into another state, form, or representation within a specific context or process.
-
C.
motherTransformedInto
Indicates that an entity’s mother has been changed or converted into another form, state, or entity.
-
D.
bodyTransformedInto
Indicates that one entity’s physical form is changed or converted into another specified form or entity.
-
E.
enchantedBy
Indicates that one entity has cast or holds a magical enchantment over 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.