Triple

T19693185
Position Surface form Disambiguated ID Type / Status
Subject Network-in-Network architecture E472886 entity
Predicate proposedBy P32 FINISHED
Object Min Lin
Min Lin is a computer scientist known for introducing the Network-in-Network deep learning architecture that advanced convolutional neural network design.
 E1389323 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: Min Lin | Statement: [Network-in-Network architecture, proposedBy, Min Lin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Min Lin
Context triple: [Network-in-Network architecture, proposedBy, Min Lin]
  • A. Sun Daolin
    Sun Daolin was a renowned Chinese film actor and director, celebrated for his performances in classic mid-20th-century Chinese cinema.
  • B. Tzu Chiang
    Tzu Chiang is the nickname of the AIDC AT-3, a Taiwanese advanced jet trainer and light attack aircraft.
  • C. Chia-Shun Yih
    Chia-Shun Yih was a prominent Chinese-American fluid dynamicist known for his influential theoretical work on hydrodynamic stability and stratified flows.
  • D. Louis Wu
    Louis Wu is a central human protagonist in Larry Niven’s Known Space science fiction series, best known for his role in the novel "Ringworld."
  • E. Chien-Po
    Chien-Po is a gentle, large, and good-natured warrior from Disney’s Mulan series, known for his calm demeanor and physical strength.
  • 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: Min Lin
Triple: [Network-in-Network architecture, proposedBy, Min Lin]
Generated description
Min Lin is a computer scientist known for introducing the Network-in-Network deep learning architecture that advanced convolutional neural network design.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Min Lin
Target entity description: Min Lin is a computer scientist known for introducing the Network-in-Network deep learning architecture that advanced convolutional neural network design.
  • A. Sun Daolin
    Sun Daolin was a renowned Chinese film actor and director, celebrated for his performances in classic mid-20th-century Chinese cinema.
  • B. Tzu Chiang
    Tzu Chiang is the nickname of the AIDC AT-3, a Taiwanese advanced jet trainer and light attack aircraft.
  • C. Chia-Shun Yih
    Chia-Shun Yih was a prominent Chinese-American fluid dynamicist known for his influential theoretical work on hydrodynamic stability and stratified flows.
  • D. Louis Wu
    Louis Wu is a central human protagonist in Larry Niven’s Known Space science fiction series, best known for his role in the novel "Ringworld."
  • E. Chien-Po
    Chien-Po is a gentle, large, and good-natured warrior from Disney’s Mulan series, known for his calm demeanor and physical strength.
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e64211e5d481908358d922e0dca271 completed April 20, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0787ce586c8190b75dbf719e9a9f3e completed May 15, 2026, 8:53 p.m.
NEDg Description generation batch_6a079103857081908bbcd7eb0d003a9a completed May 15, 2026, 9:32 p.m.
NED2 Entity disambiguation (via description) batch_6a0791f98d94819093e70884ee3b6c5c completed May 15, 2026, 9:36 p.m.
Created at: April 10, 2026, 1:46 p.m.