Triple

T38556455
Position Surface form Disambiguated ID Type / Status
Subject ARM big.LITTLE heterogeneous computing E925257 entity
Predicate usesCoreType P18973 FINISHED
Object ARM Cortex-A7
ARM Cortex-A7 is a low-power, energy-efficient 32-bit processor core widely used in mobile and embedded devices, often paired with higher-performance cores in heterogeneous multi-core architectures.
 E2274108 NE FINISHED

How this triple was built (3 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: ARM Cortex-A7 | Statement: [ARM big.LITTLE heterogeneous computing, usesCoreType, ARM Cortex-A7]
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: ARM Cortex-A7
Triple: [ARM big.LITTLE heterogeneous computing, usesCoreType, ARM Cortex-A7]
Generated description
ARM Cortex-A7 is a low-power, energy-efficient 32-bit processor core widely used in mobile and embedded devices, often paired with higher-performance cores in heterogeneous multi-core architectures.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: usesCoreType
Context triple: [ARM big.LITTLE heterogeneous computing, usesCoreType, ARM Cortex-A7]
  • A. supportsTypeOfCoreper
    Indicates that one entity provides assistance, endorsement, or backing for a particular type or configuration of a "coreper" entity.
  • B. typicalCoreType chosen
    Indicates that something is a standard or characteristic core type within a given classification or system.
  • C. hasCore
    Indicates that one entity possesses, contains, or is built around a central or most essential component represented by another entity.
  • D. usesCoreNetworkModel
    Indicates that one entity operates based on, or is implemented using, a fundamental or standardized core network model defined by another entity.
  • E. hasCoreUnit
    Indicates that an entity includes or is composed around a primary, central, or fundamental unit.
  • F. None of above.

Provenance (6 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_69f76eaeb69c8190b367df9330d6f6af completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fe920a437081908d5174e8cf7a53a6 completed May 9, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41e0418274819088dfdc4c8c0f7190 completed June 29, 2026, 3:02 a.m.
NEDg Description generation batch_6a41e0f0242c81909f8320932f505aca completed June 29, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a41e14b84e881908f0c039d5101b5e5 completed June 29, 2026, 3:06 a.m.
PD Predicate disambiguation batch_69fe919a9a6c8190acb4483f386e6db7 completed May 9, 2026, 1:44 a.m.
Created at: May 3, 2026, 4:32 p.m.