Triple

T7932948
Position Surface form Disambiguated ID Type / Status
Subject Dialogflow E184225 entity
Predicate integratesWith P1075 FINISHED
Object LINE
LINE is a popular Japanese messaging and social media platform that offers free calls, chats, stickers, and various integrated services across mobile and desktop devices.
 E697175 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: LINE | Statement: [Dialogflow, integratesWith, LINE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LINE
Context triple: [Dialogflow, integratesWith, LINE]
  • A. Business Line
    Business Line is an Indian business and financial daily newspaper known for its coverage of markets, economy, and corporate affairs.
  • B. WeChat
    WeChat is a Chinese multi-purpose mobile app developed by Tencent that combines messaging, social media, and payment services into a single platform.
  • C. BBM
    BBM was a short-lived 1990s British rock supergroup featuring Jack Bruce, Ginger Baker, and Gary Moore.
  • D. VK
    VK is a major Russian technology company best known for operating the VKontakte social networking service and other popular online platforms.
  • E. LIN
    LIN is the three-letter IATA airport code for Milan Linate Airport, one of the main airports serving Milan, Italy.
  • 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: LINE
Triple: [Dialogflow, integratesWith, LINE]
Generated description
LINE is a popular Japanese messaging and social media platform that offers free calls, chats, stickers, and various integrated services across mobile and desktop devices.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LINE
Target entity description: LINE is a popular Japanese messaging and social media platform that offers free calls, chats, stickers, and various integrated services across mobile and desktop devices.
  • A. Business Line
    Business Line is an Indian business and financial daily newspaper known for its coverage of markets, economy, and corporate affairs.
  • B. WeChat
    WeChat is a Chinese multi-purpose mobile app developed by Tencent that combines messaging, social media, and payment services into a single platform.
  • C. BBM
    BBM was a short-lived 1990s British rock supergroup featuring Jack Bruce, Ginger Baker, and Gary Moore.
  • D. VK
    VK is a major Russian technology company best known for operating the VKontakte social networking service and other popular online platforms.
  • E. LIN
    LIN is the three-letter IATA airport code for Milan Linate Airport, one of the main airports serving Milan, Italy.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3acfd2a88190b1a13cd6fdedc272 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c041e588190bfbf251ed88d5bcd completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb5f22f89c8190a98208bf096a2427 completed March 31, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69cb76d2dff8819085ad9e10baad1537 completed March 31, 2026, 7:25 a.m.
Created at: March 30, 2026, 5:08 p.m.