Triple

T4228680
Position Surface form Disambiguated ID Type / Status
Subject König E94523 entity
Predicate hasVariant P455 FINISHED
Object Koning
Koning is a Dutch surname and term meaning “king,” commonly used in the Netherlands and Belgium.
E423632 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: Koning | Statement: [König, hasVariant, Koning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koning
Context triple: [König, hasVariant, Koning]
  • A. König
    König is a German-language surname borne by numerous individuals, including notable figures in fields such as religion, science, and the arts.
  • B. Kœnig
    Kœnig is a French surname most notably associated with figures such as General Marie-Pierre Kœnig, a prominent military leader during World War II.
  • C. KING
    KING is a television station in Seattle, Washington, known for its local news coverage and affiliation with major U.S. broadcast networks.
  • D. KING
    KING is the stock ticker symbol for King Digital Entertainment, the video game company best known for creating the mobile puzzle game Candy Crush Saga.
  • E. Kir Royal
    Kir Royal is a classic French champagne cocktail typically made by combining crème de cassis with sparkling wine.
  • 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: Koning
Triple: [König, hasVariant, Koning]
Generated description
Koning is a Dutch surname and term meaning “king,” commonly used in the Netherlands and Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Koning
Target entity description: Koning is a Dutch surname and term meaning “king,” commonly used in the Netherlands and Belgium.
  • A. König
    König is a German-language surname borne by numerous individuals, including notable figures in fields such as religion, science, and the arts.
  • B. Kœnig
    Kœnig is a French surname most notably associated with figures such as General Marie-Pierre Kœnig, a prominent military leader during World War II.
  • C. KING
    KING is a television station in Seattle, Washington, known for its local news coverage and affiliation with major U.S. broadcast networks.
  • D. KING
    KING is the stock ticker symbol for King Digital Entertainment, the video game company best known for creating the mobile puzzle game Candy Crush Saga.
  • E. Kir Royal
    Kir Royal is a classic French champagne cocktail typically made by combining crème de cassis with sparkling wine.
  • 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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e51817c8190bff50f2c3b5deea0 completed March 12, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a85fdbe08190bcdc18a4bc456b59 completed March 14, 2026, 6:26 p.m.
NEDg Description generation batch_69b5a8f374fc8190830286dfadc9bdbb completed March 14, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69b5a99a4a9c8190a7e9bbc119d8d775 completed March 14, 2026, 6:31 p.m.
Created at: March 12, 2026, 11:04 p.m.