Triple

T733916
Position Surface form Disambiguated ID Type / Status
Subject Otto Hofmann E14889 entity
Predicate givenName P17 FINISHED
Object Otto
Otto is a masculine given name of Germanic origin, commonly used in German-speaking countries and historically borne by various nobles, rulers, and notable figures.
 E40924 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: Otto | Statement: [Otto Hofmann, givenName, Otto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Otto
Context triple: [Otto Hofmann, givenName, Otto]
  • A. Otto
    Otto is the central German soldier protagonist in the 1993 war film "Stalingrad," whose experiences depict the brutality and futility of the Eastern Front in World War II.
  • B. Otto
    Otto is the title of one of the early nominative reports that were later incorporated into the official United States Reports, documenting decisions of the U.S. Supreme Court.
  • C. Hermann
    Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
  • D. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • E. Ernst
    Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • 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: Otto
Triple: [Otto Hofmann, givenName, Otto]
Generated description
Otto is a masculine given name of Germanic origin, commonly used in German-speaking countries and historically borne by various nobles, rulers, and notable figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Otto
Target entity description: Otto is a masculine given name of Germanic origin, commonly used in German-speaking countries and historically borne by various nobles, rulers, and notable figures.
  • A. Otto
    Otto is the title of one of the early nominative reports that were later incorporated into the official United States Reports, documenting decisions of the U.S. Supreme Court.
  • B. Otto chosen
    Otto is the central German soldier protagonist in the 1993 war film "Stalingrad," whose experiences depict the brutality and futility of the Eastern Front in World War II.
  • C. Hermann
    Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
  • D. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • E. Ernst
    Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5d6cc58819082018cdfa14b37df completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a9338feedc8190bc5f489428babd82 completed March 5, 2026, 7:41 a.m.
NEDg Description generation batch_69a94f32b2648190992e3265a7feaf93 completed March 5, 2026, 9:38 a.m.
NED2 Entity disambiguation (via description) batch_69aabb6704048190886eea7d07b6100d completed March 6, 2026, 11:32 a.m.
Created at: March 1, 2026, 7:37 p.m.