Triple

T2952879
Position Surface form Disambiguated ID Type / Status
Subject Huber E79860 entity
Predicate hasNotableBearer P458 FINISHED
Object Peter Huber
Peter Huber is a relatively common personal name shared by multiple individuals across various professions, including law, politics, and academia.
E315088 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: Peter Huber | Statement: [Huber, hasNotableBearer, Peter Huber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Huber
Context triple: [Huber, hasNotableBearer, Peter Huber]
  • A. Philip Steuer
    Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
  • B. Michael Lehmann
    Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
  • C. Peter R. Hunt
    Peter R. Hunt was a British film editor and director best known for his long association with the James Bond series, including directing the 1969 film "On Her Majesty's Secret Service."
  • D. Peter A. Ziegler
    Peter A. Ziegler was a prominent Swiss geologist known for his influential work on the tectonic evolution and geological history of Europe.
  • E. Robert Hartmann
    Robert Hartmann is a technology entrepreneur best known as a founder of the semiconductor company Altera.
  • 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: Peter Huber
Triple: [Huber, hasNotableBearer, Peter Huber]
Generated description
Peter Huber is a relatively common personal name shared by multiple individuals across various professions, including law, politics, and academia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Peter Huber
Target entity description: Peter Huber is a relatively common personal name shared by multiple individuals across various professions, including law, politics, and academia.
  • A. Philip Steuer
    Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
  • B. Michael Lehmann
    Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
  • C. Peter R. Hunt
    Peter R. Hunt was a British film editor and director best known for his long association with the James Bond series, including directing the 1969 film "On Her Majesty's Secret Service."
  • D. Peter A. Ziegler
    Peter A. Ziegler was a prominent Swiss geologist known for his influential work on the tectonic evolution and geological history of Europe.
  • E. Robert Hartmann
    Robert Hartmann is a technology entrepreneur best known as a founder of the semiconductor company Altera.
  • 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_69ad8b1276588190a374a0b12e0f7bdf completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98fe4b688190a0f68c4f80cd6f8f completed March 8, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc82d1248190869beffffc0bf956 completed March 11, 2026, 5:24 a.m.
NEDg Description generation batch_69b0fd25e07c819088b2b1bcef4cf54e completed March 11, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_69b100ecbee081908832ddec0efdc751 completed March 11, 2026, 5:43 a.m.
Created at: March 8, 2026, 2:57 p.m.