Triple

T6910105
Position Surface form Disambiguated ID Type / Status
Subject Marcus Yallow E159907 entity
Predicate associatedWith P37 FINISHED
Object Xnet
Xnet is the underground, encrypted peer-to-peer communication network used by teens to evade government surveillance in Cory Doctorow’s novel "Little Brother."
 E628022 NE FINISHED

How this triple was built (4 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: Xnet | Statement: [Marcus Yallow, associatedWith, Xnet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Xnet
Context triple: [Marcus Yallow, associatedWith, Xnet]
  • A. Best Buy
    Best Buy is a major American consumer electronics retail chain known for selling computers, appliances, and entertainment products through large-format stores and online.
  • B. Micro Center
    Micro Center is a U.S.-based retail chain specializing in computers, consumer electronics, and related accessories.
  • C. Kogan
    Kogan is a variant form of the Jewish surname Cohen, often arising from transliteration or regional spelling differences.
  • D. Electronics City
    Electronics City is a major technology and industrial hub in Bengaluru, India, known for housing numerous IT companies and electronics manufacturing units.
  • E. Jet.com
    Jet.com was an American e-commerce company known for its dynamic pricing model and rapid growth as a Walmart-acquired online retail platform.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Xnet
Triple: [Marcus Yallow, associatedWith, Xnet]
Generated description
Xnet is the underground, encrypted peer-to-peer communication network used by teens to evade government surveillance in Cory Doctorow’s novel "Little Brother."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Xnet
Target entity description: Xnet is the underground, encrypted peer-to-peer communication network used by teens to evade government surveillance in Cory Doctorow’s novel "Little Brother."
  • A. Best Buy
    Best Buy is a major American consumer electronics retail chain known for selling computers, appliances, and entertainment products through large-format stores and online.
  • B. Micro Center
    Micro Center is a U.S.-based retail chain specializing in computers, consumer electronics, and related accessories.
  • C. Kogan
    Kogan is a variant form of the Jewish surname Cohen, often arising from transliteration or regional spelling differences.
  • D. Electronics City
    Electronics City is a major technology and industrial hub in Bengaluru, India, known for housing numerous IT companies and electronics manufacturing units.
  • E. Jet.com
    Jet.com was an American e-commerce company known for its dynamic pricing model and rapid growth as a Walmart-acquired online retail platform.
  • F. None of above. chosen

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_69c68839ccb88190b4aa5cc1aca3448f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9c00e948190b103a2b2a2738bb1 completed March 27, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c749076f6c819088b0b40dd3e208b0 completed March 28, 2026, 3:20 a.m.
NEDg Description generation batch_69c74c274258819099913ac5610730ac completed March 28, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69c74cca47b88190867550802db43ef0 completed March 28, 2026, 3:36 a.m.
Created at: March 27, 2026, 2:25 p.m.