Triple
T20874029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inverted Boomerang |
E513969
|
entity |
| Predicate | restraintPurpose |
P142197
|
FINISHED |
| Object | to secure riders during inversions |
—
|
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: to secure riders during inversions | Statement: [Inverted Boomerang, restraintPurpose, to secure riders during inversions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restraintPurpose Context triple: [Inverted Boomerang, restraintPurpose, to secure riders during inversions]
-
A.
restraintType
Indicates the specific kind or method of restraint applied in a given situation or relationship.
-
B.
restraintManufacturer
Indicates that one entity is the manufacturer or producer of a restraint device used to limit or control another entity.
-
C.
usesRestraints
Indicates that one entity applies or employs physical or procedural restraints on another entity.
-
D.
aimOfPunishment
Indicates that a specified purpose or objective is the intended goal or rationale behind a particular act of punishment.
-
E.
usedToDetain
Indicates that something serves or functioned as a means, tool, or facility for holding or confining someone against their will.
- 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_69e0b4f675cc8190b4e745225b62eb66 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c46639308190a616193f3975d453 |
completed | April 21, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:45 p.m.