Triple

T5921712
Position Surface form Disambiguated ID Type / Status
Subject The Tor Project E131712 entity
Predicate develops P73 FINISHED
Object Snowflake
Snowflake is a censorship-circumvention system that helps users access the Tor network by routing their traffic through volunteer-run proxy nodes embedded in ordinary web browsers.
 E555946 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: Snowflake | Statement: [The Tor Project, develops, Snowflake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Snowflake
Context triple: [The Tor Project, develops, Snowflake]
  • A. Snowflake
    Snowflake is a cloud-based data warehousing platform known for its scalable, high-performance analytics and separation of storage and compute.
  • B. Snowbird
    Snowbird is a major ski and snowboard resort in Utah known for its steep terrain, deep powder, and long winter season.
  • C. Snowfall
    Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
  • D. Snowlets
    Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
  • E. Carbon Glacier
    Carbon Glacier is a major valley glacier on the north slope of Mount Rainier in Washington, notable for its great thickness and low terminus elevation.
  • 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: Snowflake
Triple: [The Tor Project, develops, Snowflake]
Generated description
Snowflake is a censorship-circumvention system that helps users access the Tor network by routing their traffic through volunteer-run proxy nodes embedded in ordinary web browsers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Snowflake
Target entity description: Snowflake is a censorship-circumvention system that helps users access the Tor network by routing their traffic through volunteer-run proxy nodes embedded in ordinary web browsers.
  • A. Snowflake
    Snowflake is a cloud-based data warehousing platform known for its scalable, high-performance analytics and separation of storage and compute.
  • B. Snowbird
    Snowbird is a major ski and snowboard resort in Utah known for its steep terrain, deep powder, and long winter season.
  • C. Snowfall
    Snowfall is an American crime drama television series that explores the early days of the crack cocaine epidemic in 1980s Los Angeles.
  • D. Snowlets
    Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
  • E. Carbon Glacier
    Carbon Glacier is a major valley glacier on the north slope of Mount Rainier in Washington, notable for its great thickness and low terminus elevation.
  • 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03802ff4081908589236ba5cd196d completed March 22, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c041d4f08190863141b037b1c05f completed March 23, 2026, 4:23 a.m.
NEDg Description generation batch_69c0c1db6d548190ba4be143aa7c7905 completed March 23, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_69c0c2bdd44881909aa85589d31e771a completed March 23, 2026, 4:34 a.m.
Created at: March 22, 2026, 4 p.m.