Triple

T1390089
Position Surface form Disambiguated ID Type / Status
Subject Science Museum of Minnesota E29934 entity
Predicate abbreviation P43 FINISHED
Object SMM
SMM is a major science and technology museum in Saint Paul, Minnesota, known for its interactive exhibits and educational programs.
 E159914 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: SMM | Statement: [Science Museum of Minnesota, abbreviation, SMM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SMM
Context triple: [Science Museum of Minnesota, abbreviation, SMM]
  • A. SMMC
    SMMC is the highest-ranking enlisted Marine who serves as the senior enlisted advisor to the Commandant of the United States Marine Corps.
  • B. SMR
    SMR is the three-letter ISO 3166-1 alpha-3 country code assigned to San Marino.
  • C. SMC
    SMC is a nearby dwarf irregular galaxy and satellite of the Milky Way, visible from the Southern Hemisphere and important for studies of galactic evolution and stellar populations.
  • D. SMK
    SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
  • E. SMF
    SMF is the three-letter IATA airport code for Sacramento International Airport, the primary commercial airport serving California’s capital city.
  • 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: SMM
Triple: [Science Museum of Minnesota, abbreviation, SMM]
Generated description
SMM is a major science and technology museum in Saint Paul, Minnesota, known for its interactive exhibits and educational programs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SMM
Target entity description: SMM is a major science and technology museum in Saint Paul, Minnesota, known for its interactive exhibits and educational programs.
  • A. SMMC
    SMMC is the highest-ranking enlisted Marine who serves as the senior enlisted advisor to the Commandant of the United States Marine Corps.
  • B. SMR
    SMR is the three-letter ISO 3166-1 alpha-3 country code assigned to San Marino.
  • C. SMC
    SMC is a nearby dwarf irregular galaxy and satellite of the Milky Way, visible from the Southern Hemisphere and important for studies of galactic evolution and stellar populations.
  • D. SMK
    SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
  • E. SMF
    SMF is the three-letter IATA airport code for Sacramento International Airport, the primary commercial airport serving California’s capital city.
  • 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_69a498dc92f8819094a1108f8ac90f43 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c35e023c8190b45688796d90534b completed March 1, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde24d1d88190bd6d602923270cd1 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acded052a88190945cf7a2af019c68 completed March 8, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69acdf41eb5c819088f2203f33995ccb completed March 8, 2026, 2:30 a.m.
Created at: March 1, 2026, 7:59 p.m.