Triple
T2312599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karabiner 98k |
E51991
|
entity |
| Predicate | frontSightType |
P37994
|
FINISHED |
| Object | hooded post |
—
|
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: hooded post | Statement: [Karabiner 98k, frontSightType, hooded post]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontSightType Context triple: [Karabiner 98k, frontSightType, hooded post]
-
A.
frontType
Indicates the type or category of a front (e.g., boundary or leading side) that one entity presents or forms relative to another.
-
B.
frontSector
Indicates that one entity is located in the forward-facing sector or region relative to another entity.
-
C.
sightType
Indicates the specific kind or category of sight or visual perception associated with an entity or event.
-
D.
frontLineFeature
Indicates that the subject is a prominent or leading characteristic that stands out at the forefront relative to others.
-
E.
front
Indicates that one entity is located directly before or facing another entity along a primary viewing or movement direction.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc58e88e481908733fdf79d3f8a15 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc682d094819081a96ffb77c4c42a |
completed | March 7, 2026, 6:32 a.m. |
Created at: March 4, 2026, 7:49 p.m.