Triple

T592003
Position Surface form Disambiguated ID Type / Status
Subject Salzman E17293 entity
Predicate variantOf P4680 FINISHED
Object Salzmann
Salzmann is a German surname of likely occupational or locational origin, historically borne by various notable figures in fields such as education, theology, and the arts.
 E74106 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: Salzmann | Statement: [Salzman, variantOf, Salzmann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Salzmann
Context triple: [Salzman, variantOf, Salzmann]
  • A. Salzman
    Salzman is the surname of Linda Salzman Sagan, an American artist and writer known for co-designing the Pioneer plaque sent into space.
  • B. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • C. Löwenthal
    Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
  • D. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • E. Morgenstern
    Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
  • 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: Salzmann
Triple: [Salzman, variantOf, Salzmann]
Generated description
Salzmann is a German surname of likely occupational or locational origin, historically borne by various notable figures in fields such as education, theology, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Salzmann
Target entity description: Salzmann is a German surname of likely occupational or locational origin, historically borne by various notable figures in fields such as education, theology, and the arts.
  • A. Salzman
    Salzman is the surname of Linda Salzman Sagan, an American artist and writer known for co-designing the Pioneer plaque sent into space.
  • B. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • C. Löwenthal
    Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
  • D. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • E. Morgenstern
    Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
  • 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_69a49379d09c8190ac7e00b24e2810b1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49bbaf53081908eed240bed09f63b completed March 1, 2026, 8:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69a51554857481909c684b86b51aa126 completed March 2, 2026, 4:43 a.m.
NEDg Description generation batch_69a5163b240881909672bf4bc2ebe9cf completed March 2, 2026, 4:46 a.m.
NED2 Entity disambiguation (via description) batch_69a516a1e6508190a7ecb801f5080ddd completed March 2, 2026, 4:48 a.m.
Created at: March 1, 2026, 7:33 p.m.