Triple

T6524958
Position Surface form Disambiguated ID Type / Status
Subject Woodie Flowers E151278 entity
Predicate spouse P13 FINISHED
Object Margaret Flowers
Margaret Flowers is known as the wife of the late MIT professor and robotics education pioneer Woodie Flowers.
E692413 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: Margaret Flowers | Statement: [Woodie Flowers, spouse, Margaret Flowers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret Flowers
Context triple: [Woodie Flowers, spouse, Margaret Flowers]
  • A. Margaret Gibson
    Margaret Gibson was the wife of American actor Noah Beery, associated with the early Hollywood film era.
  • B. Margaret Tucker
    Margaret Tucker was an Aboriginal Australian activist and one of the country’s first female Indigenous authors, known for her pioneering work in civil rights and welfare for Aboriginal people.
  • C. Margaret Whitmore
    Margaret Whitmore is best known as the wife of American physician-turned-thriller novelist Robin Cook.
  • D. Margaret Ann Dixon
    Margaret Ann Dixon is best known as the wife of acclaimed Canadian film director and producer Norman Jewison.
  • E. Marjorie Fowler
    Marjorie Fowler was an American film editor known for her work on numerous Hollywood productions from the 1950s through the 1970s.
  • 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: Margaret Flowers
Triple: [Woodie Flowers, spouse, Margaret Flowers]
Generated description
Margaret Flowers is known as the wife of the late MIT professor and robotics education pioneer Woodie Flowers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Margaret Flowers
Target entity description: Margaret Flowers is known as the wife of the late MIT professor and robotics education pioneer Woodie Flowers.
  • A. Margaret Gibson
    Margaret Gibson was the wife of American actor Noah Beery, associated with the early Hollywood film era.
  • B. Margaret Tucker
    Margaret Tucker was an Aboriginal Australian activist and one of the country’s first female Indigenous authors, known for her pioneering work in civil rights and welfare for Aboriginal people.
  • C. Margaret Whitmore
    Margaret Whitmore is best known as the wife of American physician-turned-thriller novelist Robin Cook.
  • D. Margaret Ann Dixon
    Margaret Ann Dixon is best known as the wife of acclaimed Canadian film director and producer Norman Jewison.
  • E. Marjorie Fowler
    Marjorie Fowler was an American film editor known for her work on numerous Hollywood productions from the 1950s through the 1970s.
  • 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_69c687f522748190b3058405553cdabd completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ad9831f88190a2b64cf6bc8c9a11 completed March 27, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ca1b0bc2108190bdb3915c0fd94ff1 completed March 30, 2026, 6:41 a.m.
NEDg Description generation batch_69ca1b7dd1b081908e9250f0dcb6d111 completed March 30, 2026, 6:43 a.m.
NED2 Entity disambiguation (via description) batch_69ca1bcd488c8190a7c7c39ca51d199d completed March 30, 2026, 6:44 a.m.
Created at: March 27, 2026, 1:45 p.m.