Triple

T8323754
Position Surface form Disambiguated ID Type / Status
Subject Sanditon E194896 entity
Predicate mainCharacter P1183 FINISHED
Object Tom Parker
Tom Parker is an enthusiastic and somewhat impulsive entrepreneur in Jane Austen’s unfinished novel "Sanditon," whose ambitions to develop the seaside resort drive much of the story’s events.
 E726652 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: Tom Parker | Statement: [Sanditon, mainCharacter, Tom Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tom Parker
Context triple: [Sanditon, mainCharacter, Tom Parker]
  • A. Michael Parker
    Michael Parker is a film editor best known for his work on the British comedy-drama "Made in Dagenham."
  • B. Steve Parker
    Steve Parker was an American film producer and manager best known for his long marriage to actress Shirley MacLaine and his work on international film projects.
  • C. John Whitesell
    John Whitesell is an American television and film director and producer known for his work on various TV series and feature comedies.
  • D. Joel Parker
    Joel Parker is a name shared by several notable individuals, including historical American politicians and jurists.
  • E. Dell Parker
    Dell Parker is a character on the medical drama series "Private Practice," known as the Oceanside Wellness Group's receptionist and aspiring midwife.
  • 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: Tom Parker
Triple: [Sanditon, mainCharacter, Tom Parker]
Generated description
Tom Parker is an enthusiastic and somewhat impulsive entrepreneur in Jane Austen’s unfinished novel "Sanditon," whose ambitions to develop the seaside resort drive much of the story’s events.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tom Parker
Target entity description: Tom Parker is an enthusiastic and somewhat impulsive entrepreneur in Jane Austen’s unfinished novel "Sanditon," whose ambitions to develop the seaside resort drive much of the story’s events.
  • A. Michael Parker
    Michael Parker is a film editor best known for his work on the British comedy-drama "Made in Dagenham."
  • B. Steve Parker
    Steve Parker was an American film producer and manager best known for his long marriage to actress Shirley MacLaine and his work on international film projects.
  • C. John Whitesell
    John Whitesell is an American television and film director and producer known for his work on various TV series and feature comedies.
  • D. Joel Parker
    Joel Parker is a name shared by several notable individuals, including historical American politicians and jurists.
  • E. Dell Parker
    Dell Parker is a character on the medical drama series "Private Practice," known as the Oceanside Wellness Group's receptionist and aspiring midwife.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f7cf49c8190b8440ff01926a66a completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95a8f18c819090f8e47061df1f55 completed April 1, 2026, 10:01 p.m.
NEDg Description generation batch_69cdb20e46b881908d3c6b177e206e50 completed April 2, 2026, 12:02 a.m.
NED2 Entity disambiguation (via description) batch_69cdb654a2348190a41a6aebf96d8ea6 completed April 2, 2026, 12:20 a.m.
Created at: March 30, 2026, 5:56 p.m.