Triple
T18780455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Form II Makashi |
E459240
|
entity |
| Predicate | typicalGrip |
P24443
|
FINISHED |
| Object | one-handed grip |
—
|
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: one-handed grip | Statement: [Form II Makashi, typicalGrip, one-handed grip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGrip Context triple: [Form II Makashi, typicalGrip, one-handed grip]
-
A.
gripType
Indicates the manner or style in which one entity physically holds or grasps another.
-
B.
hasGripType
chosen
Indicates that one entity possesses or uses a specific type or style of grip in relation to another entity or action.
-
C.
gripFeature
Indicates that one entity has a specific grip-related characteristic or functionality in relation to another entity.
-
D.
typicalGear
Indicates that the object represents the usual or standard equipment or gear commonly associated with the subject.
-
E.
gripPatternsCount
Indicates the number of distinct grip patterns associated with or used in relation to an entity.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5933e35a481908c21f7f488e1dd99 |
completed | April 20, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69e48d1126e4819099607837ed5aadca |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.