Triple

T146685
Position Surface form Disambiguated ID Type / Status
Subject Twitter, Inc. E3345 entity
Predicate operated P1688 FINISHED
Object Vine
Vine was a short-form video hosting service and social media platform known for its looping six-second clips and significant cultural impact in the early 2010s.
 E17427 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: Vine | Statement: [Twitter, Inc., operated, Vine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vine
Context triple: [Twitter, Inc., operated, Vine]
  • A. Lick
    Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
  • B. Clementine
    Clementine is a feminine given name most famously borne by Clementine Churchill, the wife of British Prime Minister Winston Churchill.
  • C. Shuar
    Shuar is an indigenous language of the Jivaroan family spoken by the Shuar people primarily in the Amazonian regions of Ecuador and Peru.
  • D. Sparks
    Sparks is a city in northern Nevada known for its proximity to Reno and its role as a regional hub for industry, transportation, and outdoor recreation.
  • E. Tebu
    Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
  • 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: Vine
Triple: [Twitter, Inc., operated, Vine]
Generated description
Vine was a short-form video hosting service and social media platform known for its looping six-second clips and significant cultural impact in the early 2010s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vine
Target entity description: Vine was a short-form video hosting service and social media platform known for its looping six-second clips and significant cultural impact in the early 2010s.
  • A. Lick
    Lick is the nickname of Joseph Carl Robnett Licklider, a pioneering American computer scientist whose ideas helped lay the foundations for interactive computing and the internet.
  • B. Clementine
    Clementine is a feminine given name most famously borne by Clementine Churchill, the wife of British Prime Minister Winston Churchill.
  • C. Shuar
    Shuar is an indigenous language of the Jivaroan family spoken by the Shuar people primarily in the Amazonian regions of Ecuador and Peru.
  • D. Sparks
    Sparks is a city in northern Nevada known for its proximity to Reno and its role as a regional hub for industry, transportation, and outdoor recreation.
  • E. Tebu
    Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
  • 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_69a252868de4819080e21c9938bfe8b6 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a25bab43608190ba5ebfbee6b5b6e4 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2c2763ce481908c12046de9003a84 completed Feb. 28, 2026, 10:24 a.m.
NEDg Description generation batch_69a2c2f02810819092e3263ac91b5fe3 completed Feb. 28, 2026, 10:26 a.m.
NED2 Entity disambiguation (via description) batch_69a2c369498481908c4213b04aea9c97 completed Feb. 28, 2026, 10:28 a.m.
Created at: Feb. 28, 2026, 2:31 a.m.