Triple

T3810093
Position Surface form Disambiguated ID Type / Status
Subject William S. Knudsen E93111 entity
Predicate familyName P18 FINISHED
Object Knudsen
Knudsen is a Danish-origin surname borne by various notable individuals in fields such as industry, science, and the arts.
 E390473 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: Knudsen | Statement: [William S. Knudsen, familyName, Knudsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Knudsen
Context triple: [William S. Knudsen, familyName, Knudsen]
  • A. Karlssen
    Karlssen is a Scandinavian-origin surname, likely a patronymic variant related to the more common name Carlson.
  • B. Kopervik
    Kopervik is a coastal town in Rogaland county, Norway, situated on the island of Karmøy and serving as an important local commercial and administrative center.
  • C. Kretschmann
    Kretschmann is a German surname most prominently associated with actor Thomas Kretschmann, known for his roles in international film and television.
  • D. Koopmans
    Koopmans is a Dutch surname most notably associated with Nobel Prize–winning economist Tjalling C. Koopmans.
  • E. Lommel
    Lommel is a municipality and city in the Belgian province of Limburg, known for its extensive forests, sand dunes, and glass industry.
  • 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: Knudsen
Triple: [William S. Knudsen, familyName, Knudsen]
Generated description
Knudsen is a Danish-origin surname borne by various notable individuals in fields such as industry, science, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Knudsen
Target entity description: Knudsen is a Danish-origin surname borne by various notable individuals in fields such as industry, science, and the arts.
  • A. Karlssen
    Karlssen is a Scandinavian-origin surname, likely a patronymic variant related to the more common name Carlson.
  • B. Kopervik
    Kopervik is a coastal town in Rogaland county, Norway, situated on the island of Karmøy and serving as an important local commercial and administrative center.
  • C. Kretschmann
    Kretschmann is a German surname most prominently associated with actor Thomas Kretschmann, known for his roles in international film and television.
  • D. Koopmans
    Koopmans is a Dutch surname most notably associated with Nobel Prize–winning economist Tjalling C. Koopmans.
  • E. Lommel
    Lommel is a municipality and city in the Belgian province of Limburg, known for its extensive forests, sand dunes, and glass industry.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80e178081908cff71223bbf6c43 completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb33db9c81908b462ee80aaaad34 completed March 14, 2026, 6:07 a.m.
NEDg Description generation batch_69b4fc08d65081908953482b10fa5611 completed March 14, 2026, 6:11 a.m.
NED2 Entity disambiguation (via description) batch_69b4fc7d8cf081909c4447818b5363c5 completed March 14, 2026, 6:13 a.m.
Created at: March 9, 2026, 3:16 p.m.