Triple

T27559626
Position Surface form Disambiguated ID Type / Status
Subject Surface Pro Type Cover E695737 entity
Predicate relatedTo P37 FINISHED
Object Surface Go Type Cover
The Surface Go Type Cover is a slim, detachable keyboard accessory designed specifically to turn Microsoft’s Surface Go tablet into a more laptop-like device with a trackpad and protective cover.
E1777926 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: Surface Go Type Cover | Statement: [Surface Pro Type Cover, relatedTo, Surface Go Type Cover]
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: Surface Go Type Cover
Triple: [Surface Pro Type Cover, relatedTo, Surface Go Type Cover]
Generated description
The Surface Go Type Cover is a slim, detachable keyboard accessory designed specifically to turn Microsoft’s Surface Go tablet into a more laptop-like device with a trackpad and protective cover.

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_69ef5387e97c8190a9dab040d21cd048 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62fb839fc81909bdfc34aac33dcf6 completed May 2, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c5cc8ec481908b095b5289f2d301 completed May 24, 2026, 9:33 a.m.
NEDg Description generation batch_6a12c73af6348190aa55c00fcaf1d46c completed May 24, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_6a12c7d1f8e8819093ef8b94c1ec2816 completed May 24, 2026, 9:41 a.m.
Created at: April 27, 2026, 1:38 p.m.