Triple

T19811604
Position Surface form Disambiguated ID Type / Status
Subject Ka-52 E475959 entity
Predicate natoReportingName P6062 FINISHED
Object Hokum-B
Hokum-B is the NATO reporting name for the Kamov Ka-52, a Russian twin-seat, all-weather attack helicopter known for its coaxial rotor system and advanced avionics.
 E1396736 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: Hokum-B | Statement: [Ka-52, natoReportingName, Hokum-B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hokum-B
Context triple: [Ka-52, natoReportingName, Hokum-B]
  • A. Hogwallop
    Hogwallop is the surname of Pete Hogwallop, a comic supporting character from the film "O Brother, Where Art Thou?".
  • B. Horokanai
    Horokanai is a small town in northern Hokkaido, Japan, known for its heavy snowfall and production of buckwheat used in soba noodles.
  • C. Hacko
    Hacko is the nickname of Lorenz Hackenholt, an SS officer who played a key role in operating gas chambers during the Holocaust.
  • D. Hambukushu
    The Hambukushu are a Bantu-speaking ethnic group of the Okavango region in Botswana and neighboring countries, known for riverine farming, fishing, and rich oral traditions.
  • E. Bummi
    Bummi is a fictional female character who serves as the central protagonist in her story.
  • 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: Hokum-B
Triple: [Ka-52, natoReportingName, Hokum-B]
Generated description
Hokum-B is the NATO reporting name for the Kamov Ka-52, a Russian twin-seat, all-weather attack helicopter known for its coaxial rotor system and advanced avionics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hokum-B
Target entity description: Hokum-B is the NATO reporting name for the Kamov Ka-52, a Russian twin-seat, all-weather attack helicopter known for its coaxial rotor system and advanced avionics.
  • A. Hogwallop
    Hogwallop is the surname of Pete Hogwallop, a comic supporting character from the film "O Brother, Where Art Thou?".
  • B. Horokanai
    Horokanai is a small town in northern Hokkaido, Japan, known for its heavy snowfall and production of buckwheat used in soba noodles.
  • C. Hacko
    Hacko is the nickname of Lorenz Hackenholt, an SS officer who played a key role in operating gas chambers during the Holocaust.
  • D. Hambukushu
    The Hambukushu are a Bantu-speaking ethnic group of the Okavango region in Botswana and neighboring countries, known for riverine farming, fishing, and rich oral traditions.
  • E. Bummi
    Bummi is a fictional female character who serves as the central protagonist in her story.
  • 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6542c9c5c81908772e88caa067e63 completed April 20, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07ccc9f03c81908818f7d03483a650 completed May 16, 2026, 1:47 a.m.
NEDg Description generation batch_6a07ce8ceadc8190a7e1f997d8d21bfd completed May 16, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_6a07cf0327408190be73a41d2663836a completed May 16, 2026, 1:57 a.m.
Created at: April 10, 2026, 1:50 p.m.