Triple
T13212811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimura lock |
E314534
|
entity |
| Predicate | sweepApplication |
P54441
|
FINISHED |
| Object | Kimura sweep from closed guard |
—
|
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: Kimura sweep from closed guard | Statement: [Kimura lock, sweepApplication, Kimura sweep from closed guard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sweepApplication Context triple: [Kimura lock, sweepApplication, Kimura sweep from closed guard]
-
A.
sweep
Indicates that an agent uses a tool or motion to clear or move unwanted material from a surface or area.
-
B.
wasSweep
Indicates that one entity performed a sweeping action on or across another entity or area.
-
C.
isSweep
Indicates that one entity performs a sweeping action on or across another entity or area.
-
D.
exampleApplication
chosen
Indicates that something serves as a representative or illustrative instance of how an application is used or functions.
-
E.
aplicación
Indicates that one entity is the use or implementation of another entity for a specific purpose or function.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9f0f148190a0698ef27573c885 |
completed | April 10, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:17 p.m.