Triple

T2114312
Position Surface form Disambiguated ID Type / Status
Subject XMPP E42571 entity
Predicate formerlyKnownAs P65 FINISHED
Object Jabber E42571 NE FINISHED

How this triple was built (2 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: Jabber | Statement: [XMPP, formerlyKnownAs, Jabber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jabber
Context triple: [XMPP, formerlyKnownAs, Jabber]
  • A. XMPP chosen
    XMPP (Extensible Messaging and Presence Protocol) is an open, XML-based communication protocol primarily used for instant messaging, presence information, and real-time data exchange over the internet.
  • B. ICQ
    ICQ is one of the earliest popular internet instant messaging services, widely used in the late 1990s and early 2000s.
  • C. AOL Instant Messenger
    AOL Instant Messenger was a pioneering late-1990s and early-2000s instant messaging service that popularized online chat and status-based communication for mainstream internet users.
  • D. Apple iChat
    Apple iChat is Apple’s former instant messaging and video chat application for macOS that integrated AIM, Jabber, and later FaceTime-style communication features.
  • E. Chatterbug
    Chatterbug is an online language-learning platform that offers live tutoring and interactive exercises to help users practice and improve foreign language skills.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb05b51c81908a78c816f492c45c completed March 7, 2026, 5:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3076afec819091183e328cff58c8 completed March 9, 2026, 2:29 a.m.
Created at: March 4, 2026, 7:43 p.m.