Triple

T19317907
Position Surface form Disambiguated ID Type / Status
Subject Micro Center E483145 entity
Predicate sellsBrand P38689 FINISHED
Object ASUS NE NERFINISHED

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: ASUS | Statement: [Micro Center, sellsBrand, ASUS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ASUS
Context triple: [Micro Center, sellsBrand, ASUS]
  • A. ASUS chosen
    ASUS is a Taiwanese multinational technology company best known for producing computers, laptops, motherboards, and other consumer electronics and hardware devices.
  • B. Acer
    Acer is a genus of deciduous trees and shrubs best known for its maples, many of which are valued for their distinctive leaves, vibrant autumn colors, and sap used to produce maple syrup.
  • C. Acer
    Acer is a Taiwanese multinational hardware and electronics corporation best known for manufacturing laptops, desktops, monitors, and other computer-related products.
  • D. ACER
    ACER is the European Union agency that coordinates and supports national energy regulators to ensure the effective functioning of the EU’s internal energy market.
  • E. Lenovo
    Lenovo is a multinational technology company best known for manufacturing and selling personal computers, laptops, smartphones, and other consumer electronics worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e60d85046c81909d972a6b369b0c2b completed April 20, 2026, 11:27 a.m.
Created at: April 10, 2026, 1:32 p.m.