Triple

T23460577
Position Surface form Disambiguated ID Type / Status
Subject Zimbabwe Republic Police E568962 entity
Predicate abbreviation P43 FINISHED
Object ZRP
ZRP is the national police force of Zimbabwe responsible for law enforcement, public order, and crime prevention across the country.
 E1589717 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: ZRP | Statement: [Zimbabwe Republic Police, abbreviation, ZRP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZRP
Context triple: [Zimbabwe Republic Police, abbreviation, ZRP]
  • A. ZRP
    ZRP is the National Rail station code used to identify Regent’s Park station in London’s public transport system.
  • B. ZP
    ZP is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • C. RZE
    RZE is the IATA airport code for Rzeszów–Jasionka Airport, an international airport serving the city of Rzeszów in southeastern Poland.
  • D. RZO
    RZO is the ICAO airline designator used to identify Azores Airlines in international aviation operations.
  • E. ZRN
    ZRN was the ISO 4217 currency code for the New Zaire, the former monetary unit of Zaire (now the Democratic Republic of the Congo).
  • 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: ZRP
Triple: [Zimbabwe Republic Police, abbreviation, ZRP]
Generated description
ZRP is the national police force of Zimbabwe responsible for law enforcement, public order, and crime prevention across the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZRP
Target entity description: ZRP is the national police force of Zimbabwe responsible for law enforcement, public order, and crime prevention across the country.
  • A. ZRP
    ZRP is the National Rail station code used to identify Regent’s Park station in London’s public transport system.
  • B. ZP
    ZP is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • C. RZE
    RZE is the IATA airport code for Rzeszów–Jasionka Airport, an international airport serving the city of Rzeszów in southeastern Poland.
  • D. RZO
    RZO is the ICAO airline designator used to identify Azores Airlines in international aviation operations.
  • E. ZRN
    ZRN was the ISO 4217 currency code for the New Zaire, the former monetary unit of Zaire (now the Democratic Republic of the Congo).
  • 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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a69afba88190b1b1dd27d331309f completed April 29, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c824ec03c8190b7a526269f6822b1 completed May 19, 2026, 3:31 p.m.
NEDg Description generation batch_6a0ca6eee2f48190b4e03039c4c96abe completed May 19, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_6a0ca819f6dc8190852bb3c06768ac5a completed May 19, 2026, 6:12 p.m.
Created at: April 17, 2026, 5:53 p.m.