Triple
T38405709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chunk |
E901321
|
entity |
| Predicate | iconicGesture |
P78724
|
FINISHED |
| Object | lifting his shirt and jiggling his belly (Truffle Shuffle) |
—
|
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: lifting his shirt and jiggling his belly (Truffle Shuffle) | Statement: [Chunk, iconicGesture, lifting his shirt and jiggling his belly (Truffle Shuffle)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iconicGesture Context triple: [Chunk, iconicGesture, lifting his shirt and jiggling his belly (Truffle Shuffle)]
-
A.
signatureGesture
Indicates a distinctive or characteristic gesture that is uniquely associated with a particular individual or entity.
-
B.
gesture
Indicates that an entity uses a bodily movement or sign to communicate or express something to another entity.
-
C.
recognizedSignLanguage
Indicates that one entity has correctly identified or understood a sign language used or produced by another entity.
-
D.
gestureForm
chosen
Indicates the specific physical configuration or movement pattern that characterizes a particular gesture within an interaction.
-
E.
usesHandGestures
Indicates that an entity communicates or expresses itself by making deliberate movements or signals with its hands.
- 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_69f76e61e79c81908b787d83b46ab92b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd313e61c8190b174b331365b803f |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:31 p.m.