Triple

T9734167
Position Surface form Disambiguated ID Type / Status
Subject Rice E236015 entity
Predicate hasNotableBearer P458 FINISHED
Object Patricia Rice
Patricia Rice is an American author best known for her historical and contemporary romance novels, often featuring strong heroines and elements of fantasy.
E819498 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: Patricia Rice | Statement: [Rice, hasNotableBearer, Patricia Rice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patricia Rice
Context triple: [Rice, hasNotableBearer, Patricia Rice]
  • A. Patricia Blair
    Patricia Blair was an American film and television actress best known for her roles in 1960s TV series such as "Daniel Boone" and "The Rifleman."
  • B. Patricia Murray
    Patricia Murray is known as the spouse of American glass artist and sculptor Dan Dailey.
  • C. Patricia Burr
    Patricia Burr is an individual notable enough to be recognized as a bearer of the surname Burr, though specific widely known public details about her are not readily established.
  • D. Sherry Martin
    Sherry Martin is the female lead in the 1936 Fred Astaire and Ginger Rogers musical film "Follow the Fleet," known for her singing, dancing, and romantic storyline.
  • E. Patricia Haines
    Patricia Haines was a British actress known for her television and film roles in the 1950s and 1960s.
  • 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: Patricia Rice
Triple: [Rice, hasNotableBearer, Patricia Rice]
Generated description
Patricia Rice is an American author best known for her historical and contemporary romance novels, often featuring strong heroines and elements of fantasy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Patricia Rice
Target entity description: Patricia Rice is an American author best known for her historical and contemporary romance novels, often featuring strong heroines and elements of fantasy.
  • A. Patricia Blair
    Patricia Blair was an American film and television actress best known for her roles in 1960s TV series such as "Daniel Boone" and "The Rifleman."
  • B. Patricia Murray
    Patricia Murray is known as the spouse of American glass artist and sculptor Dan Dailey.
  • C. Patricia Burr
    Patricia Burr is an individual notable enough to be recognized as a bearer of the surname Burr, though specific widely known public details about her are not readily established.
  • D. Sherry Martin
    Sherry Martin is the female lead in the 1936 Fred Astaire and Ginger Rogers musical film "Follow the Fleet," known for her singing, dancing, and romantic storyline.
  • E. Patricia Haines
    Patricia Haines was a British actress known for her television and film roles in the 1950s and 1960s.
  • 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_69ca84d313e88190983ee6ffd0ef60d2 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9eebcec08190a9d4606fd26f2e19 completed April 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcc8d2288190b2a1dc3fe1185030 completed April 5, 2026, 1:37 a.m.
NEDg Description generation batch_69d1bdcea9608190ac34cdd243a68830 completed April 5, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_69d1be16f35c819089fa03073e97333e completed April 5, 2026, 1:42 a.m.
Created at: March 30, 2026, 8:22 p.m.