Triple

T7133870
Position Surface form Disambiguated ID Type / Status
Subject Royal Netherlands Marechaussee E166255 entity
Predicate shortName P43 FINISHED
Object KMar
KMar is the abbreviated name for the Royal Netherlands Marechaussee, a Dutch gendarmerie force responsible for military police duties, border security, and various national security tasks.
 E643362 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: KMar | Statement: [Royal Netherlands Marechaussee, shortName, KMar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KMar
Context triple: [Royal Netherlands Marechaussee, shortName, KMar]
  • A. M-K
    M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
  • B. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • C. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • D. MK
    MK is the commonly used abbreviation for Umkhonto we Sizwe, the former armed wing of South Africa’s African National Congress during the anti-apartheid struggle.
  • E. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • 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: KMar
Triple: [Royal Netherlands Marechaussee, shortName, KMar]
Generated description
KMar is the abbreviated name for the Royal Netherlands Marechaussee, a Dutch gendarmerie force responsible for military police duties, border security, and various national security tasks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KMar
Target entity description: KMar is the abbreviated name for the Royal Netherlands Marechaussee, a Dutch gendarmerie force responsible for military police duties, border security, and various national security tasks.
  • A. M-K
    M-K is the commonly used abbreviation for Morrison-Knudsen, a major American engineering and construction company known for large-scale infrastructure projects.
  • B. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • C. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • D. MK
    MK is the commonly used abbreviation for Umkhonto we Sizwe, the former armed wing of South Africa’s African National Congress during the anti-apartheid struggle.
  • E. MK
    MK is the two-letter ISO 3166-1 alpha-2 country code assigned to North Macedonia.
  • 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_69c68884a9388190af42f90d1c1a7151 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e68f15bc8190a4d82b8ee388f497 completed March 27, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a344fb4881908f6b6e33706e0192 completed March 28, 2026, 9:45 a.m.
NEDg Description generation batch_69c7a3f2b51c81909f058149e9bd9f0a completed March 28, 2026, 9:48 a.m.
NED2 Entity disambiguation (via description) batch_69c7a4a9e91881909df07f1c540f191e completed March 28, 2026, 9:51 a.m.
Created at: March 27, 2026, 2:45 p.m.