Triple

T757958
Position Surface form Disambiguated ID Type / Status
Subject United States Park Police E15999 entity
Predicate abbreviation P43 FINISHED
Object USPP
USPP is the federal law enforcement agency responsible for policing and protecting U.S. national parks and certain federal lands, particularly in the Washington, D.C. area.
 E90470 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: USPP | Statement: [United States Park Police, abbreviation, USPP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: USPP
Context triple: [United States Park Police, abbreviation, USPP]
  • A. USCP
    USCP is the federal law enforcement agency responsible for protecting the U.S. Capitol complex, its members, staff, and visitors.
  • B. UPP
    UPP is a reporting mark used by the Union Pacific Railroad to identify certain passenger cars and related rolling stock in its fleet.
  • C. SPP
    SPP is the Supreme People's Procuratorate of China, the highest national agency responsible for legal prosecution and supervision of law enforcement in the country.
  • D. USASC
    USASC is the commonly used abbreviation for the United States Army Signal Corps, the branch responsible for the Army’s communications and information systems.
  • E. USZ
    USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
  • 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: USPP
Triple: [United States Park Police, abbreviation, USPP]
Generated description
USPP is the federal law enforcement agency responsible for policing and protecting U.S. national parks and certain federal lands, particularly in the Washington, D.C. area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: USPP
Target entity description: USPP is the federal law enforcement agency responsible for policing and protecting U.S. national parks and certain federal lands, particularly in the Washington, D.C. area.
  • A. USCP
    USCP is the federal law enforcement agency responsible for protecting the U.S. Capitol complex, its members, staff, and visitors.
  • B. UPP
    UPP is a reporting mark used by the Union Pacific Railroad to identify certain passenger cars and related rolling stock in its fleet.
  • C. SPP
    SPP is the Supreme People's Procuratorate of China, the highest national agency responsible for legal prosecution and supervision of law enforcement in the country.
  • D. USASC
    USASC is the commonly used abbreviation for the United States Army Signal Corps, the branch responsible for the Army’s communications and information systems.
  • E. USZ
    USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a66c2e108190a754c60d2eac6676 completed March 1, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a65e44b9c88190a4481c28499860d7 completed March 3, 2026, 4:06 a.m.
NEDg Description generation batch_69a660a5d3308190ae7f1220704380eb completed March 3, 2026, 4:16 a.m.
NED2 Entity disambiguation (via description) batch_69a661116e848190b6dde5b3f7570c71 completed March 3, 2026, 4:18 a.m.
Created at: March 1, 2026, 7:37 p.m.