Triple

T9660374
Position Surface form Disambiguated ID Type / Status
Subject Royal Malaysia Police E233573 entity
Predicate abbreviation P43 FINISHED
Object PDRM
PDRM is the national police force of Malaysia responsible for maintaining law and order, crime prevention, and internal security across the country.
 E812978 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: PDRM | Statement: [Royal Malaysia Police, abbreviation, PDRM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PDRM
Context triple: [Royal Malaysia Police, abbreviation, PDRM]
  • A. Pades
    Pades is a village in northwestern Greece located in the mountainous region near Mount Smolikas.
  • B. PDM
    PDM is a modern Python package and dependency manager that emphasizes PEP 582 support and a streamlined, pyproject.toml-based workflow.
  • C. KPRM
    KPRM is the commonly used abbreviation for the Chancellery of the Prime Minister of Poland, the central office supporting the head of government.
  • D. KPKB
    KPKB is the ICAO airport code for Mid-Ohio Valley Regional Airport, a public airport serving the Parkersburg–Vienna area in West Virginia, United States.
  • E. DRS
    DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
  • 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: PDRM
Triple: [Royal Malaysia Police, abbreviation, PDRM]
Generated description
PDRM is the national police force of Malaysia responsible for maintaining law and order, crime prevention, and internal security across the country.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PDRM
Target entity description: PDRM is the national police force of Malaysia responsible for maintaining law and order, crime prevention, and internal security across the country.
  • A. Pades
    Pades is a village in northwestern Greece located in the mountainous region near Mount Smolikas.
  • B. PDM
    PDM is a modern Python package and dependency manager that emphasizes PEP 582 support and a streamlined, pyproject.toml-based workflow.
  • C. KPRM
    KPRM is the commonly used abbreviation for the Chancellery of the Prime Minister of Poland, the central office supporting the head of government.
  • D. KPKB
    KPKB is the ICAO airport code for Mid-Ohio Valley Regional Airport, a public airport serving the Parkersburg–Vienna area in West Virginia, United States.
  • E. DRS
    DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
  • 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_69ca848d3b6c8190ae98ea554dea58df completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9c08d0d0819086426ad6891b18db completed April 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18a0b84a0819083191beeaf8d968b completed April 4, 2026, 10 p.m.
NEDg Description generation batch_69d18ac0796c8190b48ccdb9c5052332 completed April 4, 2026, 10:03 p.m.
NED2 Entity disambiguation (via description) batch_69d18b7f7510819083a402d6802c7d95 completed April 4, 2026, 10:06 p.m.
Created at: March 30, 2026, 8:14 p.m.