Triple

T12209594
Position Surface form Disambiguated ID Type / Status
Subject Mr. Brown E290920 entity
Predicate spouse P13 FINISHED
Object Mary Brown
Mary Brown is the wife of Mr. Brown, known primarily in relation to him as his spouse.
E971833 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: Mary Brown | Statement: [Mr. Brown, spouse, Mary Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mary Brown
Context triple: [Mr. Brown, spouse, Mary Brown]
  • A. Mary Brown
    Mary Brown is a writer known for her contributions to contemporary literature.
  • B. Mary Bowne
    Mary Bowne was a colonial-era New Yorker known primarily as the daughter of Quaker pioneer and religious freedom advocate John Bowne.
  • C. Mary Pratt
    Mary Pratt was a prominent Canadian realist painter renowned for her luminous, intimate depictions of everyday domestic scenes.
  • D. Mary Wilkes
    Mary Wilkes is the daughter of the 18th-century English radical politician and journalist John Wilkes.
  • E. Margaret Corbin
    Margaret Corbin was an American Revolutionary War heroine who took over her fallen husband's cannon during battle, becoming one of the first women to fight in the war and receive a military pension.
  • 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: Mary Brown
Triple: [Mr. Brown, spouse, Mary Brown]
Generated description
Mary Brown is the wife of Mr. Brown, known primarily in relation to him as his spouse.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mary Brown
Target entity description: Mary Brown is the wife of Mr. Brown, known primarily in relation to him as his spouse.
  • A. Mary Brown
    Mary Brown is a writer known for her contributions to contemporary literature.
  • B. Mary Bowne
    Mary Bowne was a colonial-era New Yorker known primarily as the daughter of Quaker pioneer and religious freedom advocate John Bowne.
  • C. Mary Pratt
    Mary Pratt was a prominent Canadian realist painter renowned for her luminous, intimate depictions of everyday domestic scenes.
  • D. Mary Wilkes
    Mary Wilkes is the daughter of the 18th-century English radical politician and journalist John Wilkes.
  • E. Margaret Corbin
    Margaret Corbin was an American Revolutionary War heroine who took over her fallen husband's cannon during battle, becoming one of the first women to fight in the war and receive a military pension.
  • 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c7ed4688190b0546b784e36b0ec completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a9d2f0c81908352cd9f0167c6ab completed May 2, 2026, 2:30 p.m.
NEDg Description generation batch_69f60f2154c8819081f9cf6f51e5255b completed May 2, 2026, 2:50 p.m.
NED2 Entity disambiguation (via description) batch_69f60fe8c2ec8190af7c69dd17ea75fe completed May 2, 2026, 2:53 p.m.
Created at: April 8, 2026, 9:51 p.m.