Triple

T5442929
Position Surface form Disambiguated ID Type / Status
Subject MSG E122179 entity
Predicate hasOrgan P35 FINISHED
Object MSG Secretariat
The MSG Secretariat is the administrative and coordinating body that supports and implements the decisions and activities of the Melanesian Spearhead Group, a subregional organization in the Pacific.
 E521432 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: MSG Secretariat | Statement: [MSG, hasOrgan, MSG Secretariat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MSG Secretariat
Context triple: [MSG, hasOrgan, MSG Secretariat]
  • A. Mo the Mule
    Mo the Mule is the costumed mule mascot representing the University of Central Missouri at its athletic events and campus activities.
  • B. Marty the Zebra
    Marty the Zebra is a main character from the "Madagascar" animated film series, known as the optimistic, adventure-seeking zebra and best friend of Alex the Lion.
  • C. Marco the Bison
    Marco the Bison is the costumed buffalo mascot representing Marshall University at its athletic events and campus activities.
  • D. Bill the Goat
    Bill the Goat is the long-standing and beloved live mascot of the United States Naval Academy’s athletic teams.
  • E. Shep
    Shep is the station code used to identify Sheppard–Yonge station in the Toronto subway system.
  • 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: MSG Secretariat
Triple: [MSG, hasOrgan, MSG Secretariat]
Generated description
The MSG Secretariat is the administrative and coordinating body that supports and implements the decisions and activities of the Melanesian Spearhead Group, a subregional organization in the Pacific.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MSG Secretariat
Target entity description: The MSG Secretariat is the administrative and coordinating body that supports and implements the decisions and activities of the Melanesian Spearhead Group, a subregional organization in the Pacific.
  • A. Mo the Mule
    Mo the Mule is the costumed mule mascot representing the University of Central Missouri at its athletic events and campus activities.
  • B. Marty the Zebra
    Marty the Zebra is a main character from the "Madagascar" animated film series, known as the optimistic, adventure-seeking zebra and best friend of Alex the Lion.
  • C. Marco the Bison
    Marco the Bison is the costumed buffalo mascot representing Marshall University at its athletic events and campus activities.
  • D. Bill the Goat
    Bill the Goat is the long-standing and beloved live mascot of the United States Naval Academy’s athletic teams.
  • E. Shep
    Shep is the station code used to identify Sheppard–Yonge station in the Toronto subway system.
  • 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_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.
NEDg Description generation batch_69bf42e2bbe08190be6616a9cab6f9a0 completed March 22, 2026, 1:16 a.m.
NED2 Entity disambiguation (via description) batch_69bf4343879881909b26e716d10fbad3 completed March 22, 2026, 1:17 a.m.
Created at: March 20, 2026, 2:07 p.m.