Triple

T4269798
Position Surface form Disambiguated ID Type / Status
Subject Best Take E96912 entity
Predicate relatedTo P37 FINISHED
Object Magic Eraser E80215 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: Magic Eraser | Statement: [Best Take, relatedTo, Magic Eraser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magic Eraser
Context triple: [Best Take, relatedTo, Magic Eraser]
  • A. Magic Eraser chosen
    Magic Eraser is a Google Photos tool that uses AI to remove or camouflage unwanted objects and distractions from images.
  • B. Eraser
    Eraser is a 1996 action thriller film starring Arnold Schwarzenegger as a U.S. Marshal who protects a key witness while uncovering a high-tech weapons conspiracy.
  • C. Brillo
    Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
  • D. Chalk
    Chalk is a pale, off-white color option commonly used for consumer electronics and home devices to provide a neutral, minimalist appearance.
  • E. Wand
    Wand is an American rock band known for its eclectic blend of psychedelic, garage, and experimental sounds, often released through the independent label Drag City.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ffa30c08190913622ffec47d33d completed March 12, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7a456108190afa46344a5ed2118 completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:07 p.m.