Triple

T11529416
Position Surface form Disambiguated ID Type / Status
Subject Marine Aircraft Group 31 E273379 entity
Predicate nickname P55 FINISHED
Object MAG-31
MAG-31 is a United States Marine Corps aviation unit known as Marine Aircraft Group 31, which provides combat-ready fixed-wing aviation support.
 E932014 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: MAG-31 | Statement: [Marine Aircraft Group 31, nickname, MAG-31]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MAG-31
Context triple: [Marine Aircraft Group 31, nickname, MAG-31]
  • A. MAG-39
    MAG-39 is a United States Marine Corps aviation unit that provides helicopter and tiltrotor support for Marine Air-Ground Task Force operations.
  • B. MAG-11
    MAG-11 is a United States Marine Corps aviation unit known as Marine Aircraft Group 11, which provides combat-ready aircraft and aviation support.
  • C. MAG-26
    MAG-26 is a United States Marine Corps aviation unit that provides assault support and helicopter operations as part of the 2nd Marine Aircraft Wing.
  • D. MAG-29
    MAG-29 is a United States Marine Corps aviation unit that provides assault support and utility helicopter capabilities as part of the 2nd Marine Aircraft Wing.
  • E. MAG
    MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
  • 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: MAG-31
Triple: [Marine Aircraft Group 31, nickname, MAG-31]
Generated description
MAG-31 is a United States Marine Corps aviation unit known as Marine Aircraft Group 31, which provides combat-ready fixed-wing aviation support.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MAG-31
Target entity description: MAG-31 is a United States Marine Corps aviation unit known as Marine Aircraft Group 31, which provides combat-ready fixed-wing aviation support.
  • A. MAG-39
    MAG-39 is a United States Marine Corps aviation unit that provides helicopter and tiltrotor support for Marine Air-Ground Task Force operations.
  • B. MAG-11
    MAG-11 is a United States Marine Corps aviation unit known as Marine Aircraft Group 11, which provides combat-ready aircraft and aviation support.
  • C. MAG-26
    MAG-26 is a United States Marine Corps aviation unit that provides assault support and helicopter operations as part of the 2nd Marine Aircraft Wing.
  • D. MAG-29
    MAG-29 is a United States Marine Corps aviation unit that provides assault support and utility helicopter capabilities as part of the 2nd Marine Aircraft Wing.
  • E. MAG
    MAG is the parent company of Malaysia Airlines and related aviation businesses, overseeing the group’s airline, cargo, and aviation services operations.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d883972b10819093bd09cf8406671c completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6856341b481909d2ee71893e6117b completed April 20, 2026, 7:58 p.m.
NEDg Description generation batch_69e68fd6b6088190b24f552b5afc3f55 completed April 20, 2026, 8:43 p.m.
NED2 Entity disambiguation (via description) batch_69e6b7d683448190b7557bffd92b3ad6 completed April 20, 2026, 11:33 p.m.
Created at: April 8, 2026, 9:37 p.m.