Triple

T3250467
Position Surface form Disambiguated ID Type / Status
Subject Weiss E68163 entity
Predicate hasNotableBearer P458 FINISHED
Object Michael Weiss
Michael Weiss is a common personal name shared by multiple notable individuals across fields such as journalism, sports, and the arts.
 E372885 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 Weiss | Statement: [Weiss, hasNotableBearer, Michael Weiss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael Weiss
Context triple: [Weiss, hasNotableBearer, Michael Weiss]
  • A. Andrew Weiss
    Andrew Weiss is a notable individual whose specific prominence or field of recognition is not clearly identifiable from the given information alone.
  • B. John Weiss
    John Weiss is a relatively obscure individual whose specific notability is not clearly established from the given information.
  • C. David Weisberg
    David Weisberg is a screenwriter best known for co-writing the action film "The Rock" and other Hollywood thrillers.
  • D. David Weiss
    David Weiss is a common personal name shared by multiple notable individuals across fields such as law, music, and literature.
  • E. Steve Weissman
    Steve Weissman is an American political activist and writer best known for his leadership role in the 1964 Berkeley Free Speech Movement.
  • 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 Weiss
Triple: [Weiss, hasNotableBearer, Michael Weiss]
Generated description
Michael Weiss is a common personal name shared by multiple notable individuals across fields such as journalism, sports, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael Weiss
Target entity description: Michael Weiss is a common personal name shared by multiple notable individuals across fields such as journalism, sports, and the arts.
  • A. Andrew Weiss
    Andrew Weiss is a notable individual whose specific prominence or field of recognition is not clearly identifiable from the given information alone.
  • B. John Weiss
    John Weiss is a relatively obscure individual whose specific notability is not clearly established from the given information.
  • C. David Weisberg
    David Weisberg is a screenwriter best known for co-writing the action film "The Rock" and other Hollywood thrillers.
  • D. David Weiss
    David Weiss is a common personal name shared by multiple notable individuals across fields such as law, music, and literature.
  • E. Steve Weissman
    Steve Weissman is an American political activist and writer best known for his leadership role in the 1964 Berkeley Free Speech Movement.
  • 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_69ad858e4c708190aa31d486cfee8a6a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf40f7908190a450c3136fccb020 completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b432ebe354819097a4ddce7355b8db completed March 13, 2026, 3:53 p.m.
NEDg Description generation batch_69b438eeedc48190a7db2459b5ddd564 completed March 13, 2026, 4:18 p.m.
NED2 Entity disambiguation (via description) batch_69b4394014648190bc03d643a771395c completed March 13, 2026, 4:20 p.m.
Created at: March 8, 2026, 3:09 p.m.