Triple
T24203733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pepsi Plunge |
E600045
|
entity |
| Predicate | targetBodyPart |
P90115
|
FINISHED |
| Object | head and neck |
—
|
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: head and neck | Statement: [Pepsi Plunge, targetBodyPart, head and neck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetBodyPart Context triple: [Pepsi Plunge, targetBodyPart, head and neck]
-
A.
typicalBodyPart
Indicates that one entity is a body part that is characteristically or normally associated with another entity.
-
B.
targetsBody
chosen
Indicates that one entity is directed at, aimed at, or focused on affecting the body of another entity.
-
C.
partOfBodyWith
Indicates that one entity is a body part that belongs to, or is physically contained within, another entity.
-
D.
hasBodyRegion
Indicates that an entity possesses, includes, or is associated with a specific anatomical or bodily region.
-
E.
goalsAllowedBodyPart
Indicates that a particular body part is permitted to be used when scoring a goal in the given context.
- 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27ca38c148190ae65cd692567d43d |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:37 p.m.