Triple

T11145050
Position Surface form Disambiguated ID Type / Status
Subject The Lovely Bones E263647 entity
Predicate character P662 FINISHED
Object Ray Singh
Ray Singh is a compassionate and introspective teenage boy who serves as Susie Salmon’s first love and emotional anchor in Alice Sebold’s novel "The Lovely Bones."
 E911032 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: Ray Singh | Statement: [The Lovely Bones, character, Ray Singh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ray Singh
Context triple: [The Lovely Bones, character, Ray Singh]
  • A. Ashok Chandra
    Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
  • B. Ramesh Joshi
    Ramesh Joshi is a film editor known for his work on the Indian movie "Meghe Dhaka Tara."
  • C. Sanjiv Singh
    Sanjiv Singh is a robotics researcher and professor known for his work in autonomous systems and field robotics at Carnegie Mellon University.
  • D. Sanjiv Banga
    Sanjiv Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
  • E. Karpal Singh
    Karpal Singh was a prominent Malaysian lawyer, politician, and human rights advocate, widely known as the "Tiger of Jelutong" for his fearless courtroom and parliamentary battles.
  • 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: Ray Singh
Triple: [The Lovely Bones, character, Ray Singh]
Generated description
Ray Singh is a compassionate and introspective teenage boy who serves as Susie Salmon’s first love and emotional anchor in Alice Sebold’s novel "The Lovely Bones."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ray Singh
Target entity description: Ray Singh is a compassionate and introspective teenage boy who serves as Susie Salmon’s first love and emotional anchor in Alice Sebold’s novel "The Lovely Bones."
  • A. Ashok Chandra
    Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
  • B. Ramesh Joshi
    Ramesh Joshi is a film editor known for his work on the Indian movie "Meghe Dhaka Tara."
  • C. Sanjiv Singh
    Sanjiv Singh is a robotics researcher and professor known for his work in autonomous systems and field robotics at Carnegie Mellon University.
  • D. Sanjiv Banga
    Sanjiv Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
  • E. Karpal Singh
    Karpal Singh was a prominent Malaysian lawyer, politician, and human rights advocate, widely known as the "Tiger of Jelutong" for his fearless courtroom and parliamentary battles.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8634d5481909b114d30a542ea3f completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e496c152a081909c6ad8b2a6e41927 completed April 19, 2026, 8:48 a.m.
NEDg Description generation batch_69e49a97db808190aa22d6a103a13e58 completed April 19, 2026, 9:04 a.m.
NED2 Entity disambiguation (via description) batch_69e49d71e81c8190af73931ed30e04be completed April 19, 2026, 9:16 a.m.
Created at: April 8, 2026, 9:28 p.m.