Triple

T15311960
Position Surface form Disambiguated ID Type / Status
Subject Mud E366058 entity
Predicate cinematographyBy P1953 FINISHED
Object Adam Stone
Adam Stone is a cinematographer known for his visually striking work on films such as "Mud."
 E1150735 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: Adam Stone | Statement: [Mud, cinematographyBy, Adam Stone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Adam Stone
Context triple: [Mud, cinematographyBy, Adam Stone]
  • A. Jon Stone
    Jon Stone was an American television producer, director, and writer best known as a key creative force behind the development and early success of the children's program "Sesame Street."
  • B. Peter Stone
    Peter Stone was an American screenwriter and playwright best known for crafting witty, sophisticated scripts for films such as "Charade" and the musical "1776."
  • C. Peter Stone
    Peter Stone is an American computer scientist known for his influential work in artificial intelligence and robotics, particularly in multiagent systems and robot soccer.
  • D. Jacob Stone
    Jacob Stone is a brilliant yet unassuming polymath and art historian who serves as one of the adventurous, magic-protecting heroes in the fantasy television series "The Librarians."
  • E. Tom Stone
    Tom Stone is an American soccer coach best known for his work in women’s soccer, including collegiate and professional teams.
  • 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: Adam Stone
Triple: [Mud, cinematographyBy, Adam Stone]
Generated description
Adam Stone is a cinematographer known for his visually striking work on films such as "Mud."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Adam Stone
Target entity description: Adam Stone is a cinematographer known for his visually striking work on films such as "Mud."
  • A. Jon Stone
    Jon Stone was an American television producer, director, and writer best known as a key creative force behind the development and early success of the children's program "Sesame Street."
  • B. Peter Stone
    Peter Stone was an American screenwriter and playwright best known for crafting witty, sophisticated scripts for films such as "Charade" and the musical "1776."
  • C. Peter Stone
    Peter Stone is an American computer scientist known for his influential work in artificial intelligence and robotics, particularly in multiagent systems and robot soccer.
  • D. Jacob Stone
    Jacob Stone is a brilliant yet unassuming polymath and art historian who serves as one of the adventurous, magic-protecting heroes in the fantasy television series "The Librarians."
  • E. Tom Stone
    Tom Stone is an American soccer coach best known for his work in women’s soccer, including collegiate and professional teams.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03cd2d5a88190aead748920f93d47 completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8a3da3881909b50cfbec0543adc completed May 9, 2026, 9:04 a.m.
NEDg Description generation batch_69fefdb82b2081908084a12a58ad3477 completed May 9, 2026, 9:26 a.m.
NED2 Entity disambiguation (via description) batch_69fefe6c42708190bd893885fc5bc88e completed May 9, 2026, 9:29 a.m.
Created at: April 10, 2026, 3:16 a.m.