Triple

T2290627
Position Surface form Disambiguated ID Type / Status
Subject Alexander Grothendieck E51493 entity
Predicate knownFor P22 FINISHED
Object SGA
SGA is a monumental multi-volume seminar series on algebraic geometry, led by Alexander Grothendieck, that profoundly reshaped the foundations and methods of the field.
 E254121 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: SGA | Statement: [Alexander Grothendieck, knownFor, SGA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SGA
Context triple: [Alexander Grothendieck, knownFor, SGA]
  • A. SG
    SG is a postcode area in the United Kingdom covering parts of Hertfordshire and surrounding regions.
  • B. SGN
    SGN is the IATA airport code for Tan Son Nhat International Airport, the main international gateway serving Ho Chi Minh City, Vietnam.
  • C. SARA
    SARA is the common short name for the U.S. Superfund Amendments and Reauthorization Act, which expanded and strengthened the federal Superfund program for cleaning up hazardous waste sites.
  • D. SSA
    SSA is a professional scientific organization dedicated to advancing the study and understanding of earthquakes and seismic phenomena.
  • E. SSA
    SSA is the U.S. federal agency responsible for administering Social Security programs, including retirement, disability, and survivors benefits.
  • 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: SGA
Triple: [Alexander Grothendieck, knownFor, SGA]
Generated description
SGA is a monumental multi-volume seminar series on algebraic geometry, led by Alexander Grothendieck, that profoundly reshaped the foundations and methods of the field.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SGA
Target entity description: SGA is a monumental multi-volume seminar series on algebraic geometry, led by Alexander Grothendieck, that profoundly reshaped the foundations and methods of the field.
  • A. SG
    SG is a postcode area in the United Kingdom covering parts of Hertfordshire and surrounding regions.
  • B. SGN
    SGN is the IATA airport code for Tan Son Nhat International Airport, the main international gateway serving Ho Chi Minh City, Vietnam.
  • C. SARA
    SARA is the common short name for the U.S. Superfund Amendments and Reauthorization Act, which expanded and strengthened the federal Superfund program for cleaning up hazardous waste sites.
  • D. SSA
    SSA is a professional scientific organization dedicated to advancing the study and understanding of earthquakes and seismic phenomena.
  • E. SSA
    SSA is the U.S. federal agency responsible for administering Social Security programs, including retirement, disability, and survivors benefits.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc27536588190a74731b5537c90ee completed March 7, 2026, 6:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f210bb881909086b86b2c3017a7 completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae8018c2e88190aaacaad9adc442cf completed March 9, 2026, 8:08 a.m.
NED2 Entity disambiguation (via description) batch_69ae806fd8008190bfd6c6bcd1d0ddbd completed March 9, 2026, 8:10 a.m.
Created at: March 4, 2026, 7:48 p.m.