Triple
T11518568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Hanscom |
E273096
|
entity |
| Predicate | bodyTransformation |
P99916
|
FINISHED |
| Object | loses childhood obesity and becomes fit as an adult |
—
|
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: loses childhood obesity and becomes fit as an adult | Statement: [Ben Hanscom, bodyTransformation, loses childhood obesity and becomes fit as an adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyTransformation Context triple: [Ben Hanscom, bodyTransformation, loses childhood obesity and becomes fit as an adult]
-
A.
bodyTransformedInto
Indicates that one entity’s physical form is changed or converted into another specified form or entity.
-
B.
bodyVariant
Indicates that one entity is an alternative physical form or version of another entity’s body.
-
C.
usesTransformation
Indicates that one entity applies or relies on a specific transformation process, method, or function to operate on or convert another entity.
-
D.
bodyTreatment
Indicates a treatment or therapeutic procedure that is applied to a person's body.
-
E.
bodyContour
Indicates the shape or outline of a body as defined by its external curves and boundaries.
- F. None of above. chosen
Provenance (4 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fcf927081908ef89eff7ad833b0 |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822ef46988190a1c360da4ee14fef |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:36 p.m.