Triple

T23235034
Position Surface form Disambiguated ID Type / Status
Subject Verma module E581261 entity
Predicate roleIn P161 FINISHED
Object BGG category O
BGG category O is a fundamental category in representation theory consisting of certain highest-weight modules over a semisimple Lie algebra, central to the study of Verma modules and their homological properties.
 E1576272 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: BGG category O | Statement: [Verma module, roleIn, BGG category O]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BGG category O
Context triple: [Verma module, roleIn, BGG category O]
  • A. BGGH
    BGGH is the ICAO airport code for Nuuk Airport, the main air gateway to Greenland’s capital city.
  • B. Block O
    Block O is the famously large and energetic student cheering section for Ohio State Buckeyes football games at Ohio Stadium.
  • C. OZG
    OZG is the IATA airport code for Zagora Airport, a public airport serving the Zagora region in Morocco.
  • D. Kagel
    Kagel is a small village in the municipality of Grünheide (Mark) in the Oder-Spree district of Brandenburg, Germany.
  • E. BGC
    BGC is a modern, upscale business and lifestyle district in Taguig, Metro Manila, known for its high-rise offices, shopping centers, and vibrant urban culture.
  • 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: BGG category O
Triple: [Verma module, roleIn, BGG category O]
Generated description
BGG category O is a fundamental category in representation theory consisting of certain highest-weight modules over a semisimple Lie algebra, central to the study of Verma modules and their homological properties.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BGG category O
Target entity description: BGG category O is a fundamental category in representation theory consisting of certain highest-weight modules over a semisimple Lie algebra, central to the study of Verma modules and their homological properties.
  • A. BGGH
    BGGH is the ICAO airport code for Nuuk Airport, the main air gateway to Greenland’s capital city.
  • B. Block O
    Block O is the famously large and energetic student cheering section for Ohio State Buckeyes football games at Ohio Stadium.
  • C. OZG
    OZG is the IATA airport code for Zagora Airport, a public airport serving the Zagora region in Morocco.
  • D. Kagel
    Kagel is a small village in the municipality of Grünheide (Mark) in the Oder-Spree district of Brandenburg, Germany.
  • E. BGC
    BGC is a modern, upscale business and lifestyle district in Taguig, Metro Manila, known for its high-rise offices, shopping centers, and vibrant urban culture.
  • 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_69e2460556f88190be1744a84a84173f completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f192e8c7548190b53434eeb2620a6e completed April 29, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c3f59de808190afb414450ac32d0d completed May 19, 2026, 10:45 a.m.
NEDg Description generation batch_6a0c4008c4a881908ad49e733b549036 completed May 19, 2026, 10:48 a.m.
NED2 Entity disambiguation (via description) batch_6a0c40bece448190bb9fd1a3058a1f06 completed May 19, 2026, 10:51 a.m.
Created at: April 17, 2026, 4:09 p.m.