Triple

T32436956
Position Surface form Disambiguated ID Type / Status
Subject Sharps rifle E828897 entity
Predicate hasVariant P455 FINISHED
Object Sharps Model 1852
The Sharps Model 1852 is an early percussion breech-loading rifle and carbine variant of the Sharps series, used in the mid-19th century and noted for its improved loading speed and reliability over muzzle-loading firearms.
E828897 NE 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: Sharps Model 1852 | Statement: [Sharps rifle, hasVariant, Sharps Model 1852]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sharps Model 1852
Triple: [Sharps rifle, hasVariant, Sharps Model 1852]
Generated description
The Sharps Model 1852 is an early percussion breech-loading rifle and carbine variant of the Sharps series, used in the mid-19th century and noted for its improved loading speed and reliability over muzzle-loading firearms.

Provenance (5 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_69f3491bf298819097b610f772d54a6d completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2b79ecc8190ae89806b1ed875cc completed May 3, 2026, 3:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a346674c3948190b48f53a2d3ca791d completed June 18, 2026, 9:43 p.m.
NEDg Description generation batch_6a3466f97610819092b635dcbaf7ef69 completed June 18, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_6a3467df74088190b9d033e1534876c6 completed June 18, 2026, 9:49 p.m.
Created at: May 1, 2026, 12:55 a.m.