Triple

T1521283
Position Surface form Disambiguated ID Type / Status
Subject Pilger E32232 entity
Predicate hasNotableBearer P458 FINISHED
Object Ian Pilger
Ian Pilger is an individual notable enough to be recognized as a namesake or distinguished bearer of the surname Pilger.
 E185435 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: Ian Pilger | Statement: [Pilger, hasNotableBearer, Ian Pilger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ian Pilger
Context triple: [Pilger, hasNotableBearer, Ian Pilger]
  • A. Sam Pilger
    Sam Pilger is a British sports journalist and writer known for his coverage of football and contributions to major publications.
  • B. Peter Pilger
    Peter Pilger is an individual notable enough to be recognized as a bearer of the surname Pilger.
  • C. Thomas Pilger
    Thomas Pilger is an individual notable enough to be recognized as a namesake of the surname Pilger, though specific widely known biographical details about him are not well documented.
  • D. Kevin Pilger
    Kevin Pilger is an individual notable enough to be recognized as a namesake of the surname Pilger, though specific widely known public details about him are limited.
  • E. David Seidler
    David Seidler is a British-American screenwriter best known for writing the Academy Award-winning screenplay for the historical drama film "The King’s Speech."
  • 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: Ian Pilger
Triple: [Pilger, hasNotableBearer, Ian Pilger]
Generated description
Ian Pilger is an individual notable enough to be recognized as a namesake or distinguished bearer of the surname Pilger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ian Pilger
Target entity description: Ian Pilger is an individual notable enough to be recognized as a namesake or distinguished bearer of the surname Pilger.
  • A. Sam Pilger
    Sam Pilger is a British sports journalist and writer known for his coverage of football and contributions to major publications.
  • B. Peter Pilger
    Peter Pilger is an individual notable enough to be recognized as a bearer of the surname Pilger.
  • C. Thomas Pilger
    Thomas Pilger is an individual notable enough to be recognized as a namesake of the surname Pilger, though specific widely known biographical details about him are not well documented.
  • D. Kevin Pilger
    Kevin Pilger is an individual notable enough to be recognized as a namesake of the surname Pilger, though specific widely known public details about him are limited.
  • E. David Seidler
    David Seidler is a British-American screenwriter best known for writing the Academy Award-winning screenplay for the historical drama film "The King’s Speech."
  • 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_69a885e9b0ac819093a9806ad0efc82c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a907f071848190a5fb8fa1b97ef4de completed March 5, 2026, 4:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58b487c08190bb2b1c259bd39db0 completed March 8, 2026, 11:08 a.m.
NEDg Description generation batch_69ad5c73d7fc8190a2983c2a33b2ce01 completed March 8, 2026, 11:24 a.m.
NED2 Entity disambiguation (via description) batch_69ad5cf99a908190b8af9e7bb1949d80 completed March 8, 2026, 11:26 a.m.
Created at: March 4, 2026, 7:26 p.m.