Triple

T17345781
Position Surface form Disambiguated ID Type / Status
Subject Nagel E421684 entity
Predicate hasNotableBearer P458 FINISHED
Object Alexander Nagel — NE ONDG

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: Alexander Nagel | Statement: [Nagel, hasNotableBearer, Alexander Nagel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alexander Nagel
Context triple: [Nagel, hasNotableBearer, Alexander Nagel]
  • A. Michael Neumann
    Michael Neumann is a philosopher and political writer known for his work on ethics, logic, and critical analyses of contemporary political issues, particularly regarding the Israeli–Palestinian conflict.
  • B. Michael Reinhardt
    Michael Reinhardt is a personal name shared by multiple individuals, including professionals in fields such as music, academia, and business.
  • C. Nicholas Schiefer
    Nicholas Schiefer is a computer scientist and entrepreneur best known as a co-founder of the AI safety and research company Anthropic.
  • D. Matthias Grunsky
    Matthias Grunsky is an Austrian cinematographer known for his long-time collaboration with director Andrew Bujalski on acclaimed independent films.
  • E. Alexander Witt
    Alexander Witt is a Chilean-born cinematographer and second unit director known for his work on major Hollywood action and thriller films.
  • 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: Alexander Nagel
Triple: [Nagel, hasNotableBearer, Alexander Nagel]
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alexander Nagel
Target entity description: Alexander Nagel is an American art historian known for his influential scholarship on Renaissance and contemporary art, particularly issues of temporality, authorship, and the status of images.
  • A. Michael Neumann
    Michael Neumann is a philosopher and political writer known for his work on ethics, logic, and critical analyses of contemporary political issues, particularly regarding the Israeli–Palestinian conflict.
  • B. Michael Reinhardt
    Michael Reinhardt is a personal name shared by multiple individuals, including professionals in fields such as music, academia, and business.
  • C. Nicholas Schiefer
    Nicholas Schiefer is a computer scientist and entrepreneur best known as a co-founder of the AI safety and research company Anthropic.
  • D. Matthias Grunsky
    Matthias Grunsky is an Austrian cinematographer known for his long-time collaboration with director Andrew Bujalski on acclaimed independent films.
  • E. Alexander Witt
    Alexander Witt is a Chilean-born cinematographer and second unit director known for his work on major Hollywood action and thriller films.
  • F. None of above. chosen

Provenance (4 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_69d889d520008190a26917a95bf1c2ea completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a286d34819080c5148c220fd5a1 completed April 19, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0195546198819085804ec0b5b18040 completed May 11, 2026, 8:37 a.m.
NEDg Description generation batch_6a01965807cc819088792a88b8a099d3 in_progress May 11, 2026, 8:42 a.m.
Created at: April 10, 2026, 5:44 a.m.