Triple

T1566053
Position Surface form Disambiguated ID Type / Status
Subject He Named Me Malala E33435 entity
Predicate cinematographyBy P1953 FINISHED
Object Erich Roland
Erich Roland is a cinematographer known for his work on the documentary film "He Named Me Malala."
 E238311 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: Erich Roland | Statement: [He Named Me Malala, cinematographyBy, Erich Roland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Erich Roland
Context triple: [He Named Me Malala, cinematographyBy, Erich Roland]
  • A. Richard Heidrich
    Richard Heidrich was a German Luftwaffe general and paratroop commander in World War II, noted for leading Fallschirmjäger units in several major battles, including the Italian campaign.
  • B. Erich
    Erich is a masculine given name of German origin, commonly used in German-speaking countries and beyond.
  • C. Erich Mueller
    Erich Mueller was one of the industrial executives prosecuted for war crimes and crimes against humanity in the post–World War II Krupp Trial at Nuremberg.
  • D. Erich Bey
    Erich Bey was a German Kriegsmarine admiral during World War II, best known for commanding destroyer forces in major naval operations including the Battle of the North Cape.
  • E. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking 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: Erich Roland
Triple: [He Named Me Malala, cinematographyBy, Erich Roland]
Generated description
Erich Roland is a cinematographer known for his work on the documentary film "He Named Me Malala."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Erich Roland
Target entity description: Erich Roland is a cinematographer known for his work on the documentary film "He Named Me Malala."
  • A. Richard Heidrich
    Richard Heidrich was a German Luftwaffe general and paratroop commander in World War II, noted for leading Fallschirmjäger units in several major battles, including the Italian campaign.
  • B. Erich
    Erich is a masculine given name of German origin, commonly used in German-speaking countries and beyond.
  • C. Erich Mueller
    Erich Mueller was one of the industrial executives prosecuted for war crimes and crimes against humanity in the post–World War II Krupp Trial at Nuremberg.
  • D. Erich Bey
    Erich Bey was a German Kriegsmarine admiral during World War II, best known for commanding destroyer forces in major naval operations including the Battle of the North Cape.
  • E. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • 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_69a885f11b048190935025a035302715 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb2308bec81909d1660934eff171b completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58ac128881909a2e75524682c1c9 completed March 9, 2026, 5:20 a.m.
NEDg Description generation batch_69ae5944543081909622e93012a31766 completed March 9, 2026, 5:23 a.m.
NED2 Entity disambiguation (via description) batch_69ae59d0fb688190858c764517aea035 completed March 9, 2026, 5:25 a.m.
Created at: March 4, 2026, 7:27 p.m.