Triple

T1285600
Position Surface form Disambiguated ID Type / Status
Subject Maryland State Police E27426 entity
Predicate abbreviation P43 FINISHED
Object MSP
MSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety in Maryland.
 E146395 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: MSP | Statement: [Maryland State Police, abbreviation, MSP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MSP
Context triple: [Maryland State Police, abbreviation, MSP]
  • A. MSP
    MSP stands for Member of the Scottish Parliament, an elected representative in Scotland's devolved legislature.
  • B. MSP
    MSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety across the Commonwealth of Massachusetts.
  • C. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • D. MSA
    MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
  • E. MSA
    MSA is the common abbreviation for the Master Settlement Agreement, a landmark 1998 legal settlement between major U.S. tobacco companies and state attorneys general that reshaped tobacco advertising and funded public health initiatives.
  • 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: MSP
Triple: [Maryland State Police, abbreviation, MSP]
Generated description
MSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety in Maryland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MSP
Target entity description: MSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety in Maryland.
  • A. MSP
    MSP is the primary statewide law enforcement agency responsible for highway patrol, criminal investigations, and public safety across the Commonwealth of Massachusetts.
  • B. MSP
    MSP stands for Member of the Scottish Parliament, an elected representative in Scotland's devolved legislature.
  • C. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • D. MSA
    MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
  • E. MSA
    MSA is the common abbreviation for the Master Settlement Agreement, a landmark 1998 legal settlement between major U.S. tobacco companies and state attorneys general that reshaped tobacco advertising and funded public health initiatives.
  • 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_69a496d4ec448190ad653b2590c46711 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b85eb48190a8b61dc397fa6390 completed March 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca3004b648190a4148b0421699bf9 completed March 7, 2026, 10:13 p.m.
NEDg Description generation batch_69aca3a539848190a17e8bd578bc237a completed March 7, 2026, 10:16 p.m.
NED2 Entity disambiguation (via description) batch_69aca4158bbc8190bd1f5799715e3e4c completed March 7, 2026, 10:17 p.m.
Created at: March 1, 2026, 7:51 p.m.