Triple

T28901956
Position Surface form Disambiguated ID Type / Status
Subject iPad (6th generation) E732971 entity
Predicate coprocessor P8608 FINISHED
Object Apple M10 motion coprocessor
The Apple M10 motion coprocessor is a low-power chip designed to continuously process motion and sensor data, offloading these tasks from the main processor to improve efficiency and battery life in Apple devices.
E1839780 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: Apple M10 motion coprocessor | Statement: [iPad (6th generation), coprocessor, Apple M10 motion coprocessor]
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: Apple M10 motion coprocessor
Triple: [iPad (6th generation), coprocessor, Apple M10 motion coprocessor]
Generated description
The Apple M10 motion coprocessor is a low-power chip designed to continuously process motion and sensor data, offloading these tasks from the main processor to improve efficiency and battery life in Apple devices.

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_69f05b08c2008190ac426a035a2ed66d completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65aa8deec8190b1eef143e10c9598 completed May 2, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24d40ffd648190a2c5c08a75009c1d completed June 7, 2026, 2:14 a.m.
NEDg Description generation batch_6a24d85c0b6c8190981484ea9cab005b completed June 7, 2026, 2:33 a.m.
NED2 Entity disambiguation (via description) batch_6a24dc3904c8819083e4eed8b2371d03 completed June 7, 2026, 2:49 a.m.
Created at: April 28, 2026, 8:03 a.m.