Triple

T10096227
Position Surface form Disambiguated ID Type / Status
Subject Socialcam E215873 entity
Predicate competitor P1375 FINISHED
Object Viddy
Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
E841356 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: Viddy | Statement: [Socialcam, competitor, Viddy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viddy
Context triple: [Socialcam, competitor, Viddy]
  • A. VIDO
    VIDO is a Canadian research organization at the University of Saskatchewan specializing in vaccine development and infectious disease research for both humans and animals.
  • B. Vdio
    Vdio was an online video-on-demand and streaming service launched by Skype and Rdio co-founder Janus Friis as an attempt to compete with platforms like Netflix.
  • C. VIDN
    VIDN is the four-letter ICAO airport code assigned to Noida International Airport in Uttar Pradesh, India.
  • D. The Vine
    The Vine is a public transit service brand used by C-TRAN for its bus and related transportation services in the Vancouver, Washington area.
  • E. Movima
    Movima is an indigenous language of the Bolivian lowlands, spoken by the Movima people primarily in the Beni Department.
  • 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: Viddy
Triple: [Socialcam, competitor, Viddy]
Generated description
Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Viddy
Target entity description: Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
  • A. VIDO
    VIDO is a Canadian research organization at the University of Saskatchewan specializing in vaccine development and infectious disease research for both humans and animals.
  • B. Vdio
    Vdio was an online video-on-demand and streaming service launched by Skype and Rdio co-founder Janus Friis as an attempt to compete with platforms like Netflix.
  • C. VIDN
    VIDN is the four-letter ICAO airport code assigned to Noida International Airport in Uttar Pradesh, India.
  • D. The Vine
    The Vine is a public transit service brand used by C-TRAN for its bus and related transportation services in the Vancouver, Washington area.
  • E. Movima
    Movima is an indigenous language of the Bolivian lowlands, spoken by the Movima people primarily in the Beni Department.
  • 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_69ca83a4947c8190823a7495dc5d96ed completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd0798c248190af675e30e280daa8 completed April 2, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b6b8d604819094db099981219e72 completed April 5, 2026, 7:23 p.m.
NEDg Description generation batch_69d2b8a728bc8190b9baf93a40c00642 completed April 5, 2026, 7:31 p.m.
NED2 Entity disambiguation (via description) batch_69d2b90a1de88190b7c8cf6356ffc376 completed April 5, 2026, 7:33 p.m.
Created at: March 30, 2026, 9:02 p.m.