Triple

T5442901
Position Surface form Disambiguated ID Type / Status
Subject MSG E122179 entity
Predicate shortName P43 FINISHED
Object MSG E83474 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: MSG | Statement: [MSG, shortName, MSG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MSG
Context triple: [MSG, shortName, MSG]
  • A. MSG chosen
    MSG is a famous multi-purpose indoor arena in New York City known for hosting major sports events, concerts, and entertainment spectacles.
  • B. MSG
    MSG is a subregional political and economic organization that promotes cooperation and solidarity among Melanesian countries and territories in the Pacific.
  • C. MSG
    MSG refers to U.S. Marine Security Guards, specialized Marine Corps personnel assigned to protect American embassies, consulates, and other diplomatic facilities worldwide.
  • D. MSGS
    MSGS is the stock ticker symbol for Madison Square Garden Sports Corp., a publicly traded company that owns and operates professional sports franchises and related entertainment assets.
  • E. Messages
    Messages is Apple’s built-in messaging app for iOS, iPadOS, and macOS that supports SMS, MMS, and iMessage communication across Apple devices.
  • 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_69bd4640f52c81909e653ec361f66d76 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91cb5eec8190bdf2ef0bdea84a62 completed March 20, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf41302d588190afa5906d0e3dd891 completed March 22, 2026, 1:09 a.m.
Created at: March 20, 2026, 2:07 p.m.