Triple

T1682690
Position Surface form Disambiguated ID Type / Status
Subject Kevin Systrom E36371 entity
Predicate coFounded P104 FINISHED
Object Burbn
Burbn was a location-based photo-sharing startup that served as the precursor to and foundation for what became Instagram.
 E189289 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: Burbn | Statement: [Kevin Systrom, coFounded, Burbn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Burbn
Context triple: [Kevin Systrom, coFounded, Burbn]
  • A. Flurry
    Flurry is a mobile analytics and advertising platform known for providing app usage insights and monetization tools to developers.
  • B. Friendster
    Friendster was one of the earliest major social networking websites, popular in the early 2000s for connecting friends online before eventually declining and shutting down.
  • C. Hi5
    Hi5 is a social networking website that gained popularity in the mid-2000s as an alternative platform for connecting and sharing with friends online.
  • D. Bigfire
    Bigfire is a rustic, American-style restaurant at Universal CityWalk Orlando known for its open-fire cooking and wood-smoked dishes.
  • E. Province 5
    Province 5 is one of the administrative provinces of Nepal, located in the western part of the country and known for its diverse geography and cultural heritage.
  • 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: Burbn
Triple: [Kevin Systrom, coFounded, Burbn]
Generated description
Burbn was a location-based photo-sharing startup that served as the precursor to and foundation for what became Instagram.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Burbn
Target entity description: Burbn was a location-based photo-sharing startup that served as the precursor to and foundation for what became Instagram.
  • A. Flurry
    Flurry is a mobile analytics and advertising platform known for providing app usage insights and monetization tools to developers.
  • B. Friendster
    Friendster was one of the earliest major social networking websites, popular in the early 2000s for connecting friends online before eventually declining and shutting down.
  • C. Hi5
    Hi5 is a social networking website that gained popularity in the mid-2000s as an alternative platform for connecting and sharing with friends online.
  • D. Bigfire
    Bigfire is a rustic, American-style restaurant at Universal CityWalk Orlando known for its open-fire cooking and wood-smoked dishes.
  • E. Province 5
    Province 5 is one of the administrative provinces of Nepal, located in the western part of the country and known for its diverse geography and cultural heritage.
  • 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_69a886139ed081909af0940aa9313512 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa627ab38081909d5f264ca49e036a completed March 6, 2026, 5:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71bf1998819094d3eb67c6e6bafd completed March 8, 2026, 12:55 p.m.
NEDg Description generation batch_69ad7298ee288190b5e2b7d2ccb17a91 completed March 8, 2026, 12:59 p.m.
NED2 Entity disambiguation (via description) batch_69ad7305c7b48190a8a443dbc20ec9b2 completed March 8, 2026, 1 p.m.
Created at: March 4, 2026, 7:29 p.m.