Triple
T8729761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NLAW |
E207221
|
entity |
| Predicate | sightFeature |
P20282
|
FINISHED |
| Object | integrated 2.5x magnification sight |
—
|
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: integrated 2.5x magnification sight | Statement: [NLAW, sightFeature, integrated 2.5x magnification sight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sightFeature Context triple: [NLAW, sightFeature, integrated 2.5x magnification sight]
-
A.
sightType
chosen
Indicates the specific kind or category of sight or visual perception associated with an entity or event.
-
B.
sceneFeature
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
C.
sights
Indicates that one entity perceives or observes another entity or object using vision.
-
D.
hasScenicViewOf
Indicates that one entity offers a visually appealing or picturesque view of another entity.
-
E.
surfaceFeatureOf
Indicates that one entity is a surface-level characteristic, pattern, or feature belonging to or present on another 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d19fdc88190860e0c9c93ab79ce |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:37 p.m.