Triple

T16570993
Position Surface form Disambiguated ID Type / Status
Subject Martin Hoffman E402582 entity
Predicate hasSurnameVariant P457 FINISHED
Object Hofman
Hofman is a surname of likely Germanic or Dutch origin borne by various individuals across different countries.
E1225072 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: Hofman | Statement: [Martin Hoffman, hasSurnameVariant, Hofman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hofman
Context triple: [Martin Hoffman, hasSurnameVariant, Hofman]
  • A. Hofmann
    Hofmann is a German-language surname borne by numerous notable individuals across fields such as music, science, and the arts.
  • B. Hoffman
    Hoffman is a common German-origin surname borne by numerous notable individuals across fields such as business, entertainment, science, and politics.
  • C. Hoffmann
    Hoffmann is a common German surname borne by numerous notable figures in fields such as science, literature, music, and politics.
  • D. Hammann
    Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
  • E. Hofmański
    Hofmański is a Polish surname most notably borne by Piotr Hofmański, a prominent jurist and former president of the International Criminal Court.
  • 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: Hofman
Triple: [Martin Hoffman, hasSurnameVariant, Hofman]
Generated description
Hofman is a surname of likely Germanic or Dutch origin borne by various individuals across different countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hofman
Target entity description: Hofman is a surname of likely Germanic or Dutch origin borne by various individuals across different countries.
  • A. Hofmann
    Hofmann is a German-language surname borne by numerous notable individuals across fields such as music, science, and the arts.
  • B. Hoffman
    Hoffman is a common German-origin surname borne by numerous notable individuals across fields such as business, entertainment, science, and politics.
  • C. Hoffmann
    Hoffmann is a common German surname borne by numerous notable figures in fields such as science, literature, music, and politics.
  • D. Hammann
    Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
  • E. Hofmański
    Hofmański is a Polish surname most notably borne by Piotr Hofmański, a prominent jurist and former president of the International Criminal Court.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35958d49c8190b995188240fb355b completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007da4b60c8190a682d20aa881792c completed May 10, 2026, 12:44 p.m.
NEDg Description generation batch_6a00805a84388190ac989129745e8234 completed May 10, 2026, 12:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0080abae0c81908c827dced1b56aa6 completed May 10, 2026, 12:57 p.m.
Created at: April 10, 2026, 5:16 a.m.