Triple

T5594156
Position Surface form Disambiguated ID Type / Status
Subject Crowell E146952 entity
Predicate hasNotableBearer P458 FINISHED
Object Andrew Crowell
Andrew Crowell is an individual notable enough to be specifically referenced as a bearer of the Crowell surname.
 E529816 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: Andrew Crowell | Statement: [Crowell, hasNotableBearer, Andrew Crowell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Andrew Crowell
Context triple: [Crowell, hasNotableBearer, Andrew Crowell]
  • A. Colin Kroll
    Colin Kroll was an American technology entrepreneur best known as the co-founder of the short-form video platform Vine and the mobile trivia game HQ Trivia.
  • B. Michael Andrews
    Michael Andrews is an American film composer and musician known for his atmospheric scores for movies such as Donnie Darko and Bridesmaids.
  • C. Michael Andrews
    Michael Andrews was a prominent British painter associated with the School of London, known for his psychologically charged figurative works and atmospheric landscapes.
  • D. Sam McCandlish
    Sam McCandlish is a machine learning researcher known for his work on large-scale language models and contributions to influential AI research at OpenAI.
  • E. Andrew Dunn
    Andrew Dunn is a British cinematographer known for his work on numerous high-profile films and television productions.
  • 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: Andrew Crowell
Triple: [Crowell, hasNotableBearer, Andrew Crowell]
Generated description
Andrew Crowell is an individual notable enough to be specifically referenced as a bearer of the Crowell surname.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Andrew Crowell
Target entity description: Andrew Crowell is an individual notable enough to be specifically referenced as a bearer of the Crowell surname.
  • A. Colin Kroll
    Colin Kroll was an American technology entrepreneur best known as the co-founder of the short-form video platform Vine and the mobile trivia game HQ Trivia.
  • B. Michael Andrews
    Michael Andrews is an American film composer and musician known for his atmospheric scores for movies such as Donnie Darko and Bridesmaids.
  • C. Michael Andrews
    Michael Andrews was a prominent British painter associated with the School of London, known for his psychologically charged figurative works and atmospheric landscapes.
  • D. Sam McCandlish
    Sam McCandlish is a machine learning researcher known for his work on large-scale language models and contributions to influential AI research at OpenAI.
  • E. Andrew Dunn
    Andrew Dunn is a British cinematographer known for his work on numerous high-profile films and television productions.
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020bc41408190bc990da8ddeb931e completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0286b4d2c8190a3224f3082316dc8 completed March 22, 2026, 5:35 p.m.
NEDg Description generation batch_69c0372e86c08190bf586256cab23d22 completed March 22, 2026, 6:38 p.m.
NED2 Entity disambiguation (via description) batch_69c038e7df488190a960266045c4f41f completed March 22, 2026, 6:46 p.m.
Created at: March 22, 2026, 3:38 p.m.