Triple

T20161288
Position Surface form Disambiguated ID Type / Status
Subject Albert George Wilson E491708 entity
Predicate givenName P17 FINISHED
Object Albert
Albert is a masculine given name of Germanic origin, commonly used in many European languages and associated with historical figures such as scientists, royals, and statesmen.
 E270293 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: Albert | Statement: [Albert George Wilson, givenName, Albert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Albert
Context triple: [Albert George Wilson, givenName, Albert]
  • A. Albert
    Albert was the given name of Albert I of Habsburg, a medieval King of Germany and member of the influential Habsburg dynasty.
  • B. Albert
    Albert is the first name of American television personality and longtime weather anchor Al Roker.
  • C. Albert
    Albert is the given name of the influential economist and social scientist Albert O. Hirschman.
  • D. Albert
    Albert is the given name of Albert Grey, 4th Earl Grey, a British nobleman and colonial administrator.
  • E. Albert
    Albert is the given name of French filmmaker and writer Albert Lamorisse, best known for directing the classic short film "The Red Balloon."
  • 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: Albert
Triple: [Albert George Wilson, givenName, Albert]
Generated description
Albert is a masculine given name of Germanic origin, commonly used in many European languages and associated with historical figures such as scientists, royals, and statesmen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Albert
Target entity description: Albert is a masculine given name of Germanic origin, commonly used in many European languages and associated with historical figures such as scientists, royals, and statesmen.
  • A. Albert chosen
    Albert is a masculine given name of Germanic origin, commonly used in many European languages and English-speaking countries.
  • B. Albert
    Albert is a surname of Germanic origin borne by various notable individuals across fields such as sports, politics, and the arts.
  • C. Albert
    Albert is the given name of the renowned theoretical physicist Albert Einstein, whose work revolutionized modern physics.
  • D. Albert
    Albert was the given name of Albert I of Habsburg, a medieval King of Germany and member of the influential Habsburg dynasty.
  • E. Albert
    Albert was the given name of Prince Albert of Prussia, a 19th-century Prussian royal and military figure from the House of Hohenzollern.
  • F. None of above.

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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667e43940819080f6a0b7331aaab0 completed April 20, 2026, 5:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08347b41d8819086bd36e5e04c69ad completed May 16, 2026, 9:10 a.m.
NEDg Description generation batch_6a08359866c481908aa30ac61e18bcb0 completed May 16, 2026, 9:15 a.m.
NED2 Entity disambiguation (via description) batch_6a08361f64a08190af3305685a50f001 completed May 16, 2026, 9:17 a.m.
Created at: April 11, 2026, 11:34 p.m.