Triple
T19114556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rimfire Sporter Matches |
E467873
|
entity |
| Predicate | allowsSightsType |
P20282
|
FINISHED |
| Object | iron sights |
—
|
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: iron sights | Statement: [Rimfire Sporter Matches, allowsSightsType, iron sights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowsSightsType Context triple: [Rimfire Sporter Matches, allowsSightsType, iron sights]
-
A.
hasSights
Indicates that an entity possesses or features notable sights, attractions, or points of interest.
-
B.
sightType
chosen
Indicates the specific kind or category of sight or visual perception associated with an entity or event.
-
C.
sights
Indicates that one entity perceives or observes another entity or object using vision.
-
D.
typicalSights
Indicates that certain sights or visual features are commonly or characteristically observed in association with a given entity or context.
-
E.
hasScenicAccessTo
Indicates that one place or object provides a visually appealing or notable view of another place or object.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e39617408190b5134918f54f9c52 |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b085288190b974d649e12e0844 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.