Triple

T10551019
Position Surface form Disambiguated ID Type / Status
Subject Secretaría de Seguridad Pública E248945 entity
Predicate shortName P43 FINISHED
Object SSP
SSP is the commonly used acronym for Mexico’s Secretaría de Seguridad Pública, the federal public security ministry responsible for national policing and crime prevention.
E870250 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: SSP | Statement: [Secretaría de Seguridad Pública, shortName, SSP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SSP
Context triple: [Secretaría de Seguridad Pública, shortName, SSP]
  • A. SSP
    SSP is the acronym for the Species Survival Plan, a conservation program coordinated by zoos and aquariums to manage and protect threatened and endangered species in human care.
  • B. SSP
    SSP is a communication protocol used in Serial Attached SCSI (SAS) systems to transport SCSI commands and data between storage devices and controllers.
  • C. SSP
    SSP is the official currency code for the South Sudanese pound, the legal tender of South Sudan.
  • D. SSP
    SSP is the stock ticker symbol for The E. W. Scripps Company, a major American media enterprise focused on television broadcasting and related digital media.
  • E. SPS
    SPS is the commonly used abbreviation for Seattle Public Schools, the primary public school district serving the city of Seattle, Washington.
  • 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: SSP
Triple: [Secretaría de Seguridad Pública, shortName, SSP]
Generated description
SSP is the commonly used acronym for Mexico’s Secretaría de Seguridad Pública, the federal public security ministry responsible for national policing and crime prevention.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SSP
Target entity description: SSP is the commonly used acronym for Mexico’s Secretaría de Seguridad Pública, the federal public security ministry responsible for national policing and crime prevention.
  • A. SSP
    SSP is the acronym for the Species Survival Plan, a conservation program coordinated by zoos and aquariums to manage and protect threatened and endangered species in human care.
  • B. SSP
    SSP is the stock ticker symbol for The E. W. Scripps Company, a major American media enterprise focused on television broadcasting and related digital media.
  • C. SSP
    SSP is a communication protocol used in Serial Attached SCSI (SAS) systems to transport SCSI commands and data between storage devices and controllers.
  • D. SSP
    SSP is the official currency code for the South Sudanese pound, the legal tender of South Sudan.
  • E. SPS
    SPS is a high-energy circular particle accelerator at CERN that serves as a key injector for the Large Hadron Collider and supports a wide range of physics experiments.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d526d4c4048190a104d6e088f565b3 completed April 7, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d934639b3481908204db41101132c3 completed April 10, 2026, 5:33 p.m.
NEDg Description generation batch_69d938c8b25c8190bb048053d8668e5c completed April 10, 2026, 5:52 p.m.
NED2 Entity disambiguation (via description) batch_69d939b1844881908c8fbcb9488863f6 completed April 10, 2026, 5:56 p.m.
Created at: April 6, 2026, 12:34 p.m.