Triple

T731150
Position Surface form Disambiguated ID Type / Status
Subject Ludwig Mies van der Rohe E14831 entity
Predicate father P120 FINISHED
Object Michael Mies
Michael Mies was the son of the influential modernist architect Ludwig Mies van der Rohe.
 E203183 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: Michael Mies | Statement: [Ludwig Mies van der Rohe, father, Michael Mies]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael Mies
Context triple: [Ludwig Mies van der Rohe, father, Michael Mies]
  • A. Philip Moeller
    Philip Moeller was an American theater director, playwright, and producer best known as a co-founder and key creative force behind New York’s influential Theatre Guild in the early 20th century.
  • B. 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.
  • C. Robert Ochsenfeld
    Robert Ochsenfeld was a German physicist best known for co-discovering the Meissner effect, a fundamental phenomenon in superconductivity.
  • D. Dean Riesner
    Dean Riesner was an American screenwriter best known for his work on films such as "Dirty Harry" and "Play Misty for Me."
  • E. Daniel Kraft
    Daniel Kraft is a physician-scientist, inventor, and healthcare entrepreneur known for his work in medical innovation and digital health technologies.
  • 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: Michael Mies
Triple: [Ludwig Mies van der Rohe, father, Michael Mies]
Generated description
Michael Mies was the son of the influential modernist architect Ludwig Mies van der Rohe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael Mies
Target entity description: Michael Mies was the son of the influential modernist architect Ludwig Mies van der Rohe.
  • A. Philip Moeller
    Philip Moeller was an American theater director, playwright, and producer best known as a co-founder and key creative force behind New York’s influential Theatre Guild in the early 20th century.
  • B. 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.
  • C. Robert Ochsenfeld
    Robert Ochsenfeld was a German physicist best known for co-discovering the Meissner effect, a fundamental phenomenon in superconductivity.
  • D. Dean Riesner
    Dean Riesner was an American screenwriter best known for his work on films such as "Dirty Harry" and "Play Misty for Me."
  • E. Daniel Kraft
    Daniel Kraft is a physician-scientist, inventor, and healthcare entrepreneur known for his work in medical innovation and digital health technologies.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5c40b6481909db9efd7310850b3 completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69adbf2ffb088190a49686609d7de213 completed March 8, 2026, 6:25 p.m.
NEDg Description generation batch_69adbff135188190908058a2e2d41a1e completed March 8, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69adc0832cd881909702f380412702d5 completed March 8, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:37 p.m.