Triple
T11924900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmet Catch |
E283753
|
entity |
| Predicate | catchType |
P5909
|
FINISHED |
| Object | one-handed catch |
—
|
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 catch | Statement: [Helmet Catch, catchType, one-handed catch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: catchType Context triple: [Helmet Catch, catchType, one-handed catch]
-
A.
canBeCaughtWith
Indicates that one entity is capable of being captured, obtained, or discovered using another specified entity or method.
-
B.
trapType
Indicates the specific kind or category of trap associated with an entity or situation.
-
C.
throws
Indicates that one entity propels or hurls another entity or object through space, typically by a deliberate physical action.
-
D.
catches
chosen
Indicates that one entity successfully seizes, intercepts, or takes hold of another entity, often stopping its motion or preventing its escape.
-
E.
castingType
Indicates the specific method or category of casting used to transform or represent one entity in terms of another.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e8e2fc648190a446c1917db1c7d9 |
completed | April 10, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.