Triple

T3471705
Position Surface form Disambiguated ID Type / Status
Subject Isabella Beecher Hooker E73275 entity
Predicate familyName P18 FINISHED
Object Hooker
Hooker is a surname most notably associated with members of the prominent American Beecher family, including women’s rights advocate Isabella Beecher Hooker.
 E361387 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: Hooker | Statement: [Isabella Beecher Hooker, familyName, Hooker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hooker
Context triple: [Isabella Beecher Hooker, familyName, Hooker]
  • A. Sucker
    Sucker is a 2015 Australian comedy film about a teenage conman who becomes entangled with a charismatic swindler and his enigmatic daughter.
  • B. Sucker
    "Sucker" is a 2019 upbeat pop single by the Jonas Brothers that marked their high-profile comeback and became a chart-topping hit.
  • C. Honest John
    Honest John is a sly, manipulative fox con artist who deceives Pinocchio in Disney’s adaptation of the classic tale.
  • D. Blatch
    Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
  • E. Slick Willie
    Slick Willie is the notorious nickname of American bank robber Willie Sutton, famed for his prolific Depression-era heists and clever escapes.
  • 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: Hooker
Triple: [Isabella Beecher Hooker, familyName, Hooker]
Generated description
Hooker is a surname most notably associated with members of the prominent American Beecher family, including women’s rights advocate Isabella Beecher Hooker.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hooker
Target entity description: Hooker is a surname most notably associated with members of the prominent American Beecher family, including women’s rights advocate Isabella Beecher Hooker.
  • A. Sucker
    Sucker is a 2015 Australian comedy film about a teenage conman who becomes entangled with a charismatic swindler and his enigmatic daughter.
  • B. Sucker
    "Sucker" is a 2019 upbeat pop single by the Jonas Brothers that marked their high-profile comeback and became a chart-topping hit.
  • C. Honest John
    Honest John is a sly, manipulative fox con artist who deceives Pinocchio in Disney’s adaptation of the classic tale.
  • D. Blatch
    Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
  • E. Slick Willie
    Slick Willie is the notorious nickname of American bank robber Willie Sutton, famed for his prolific Depression-era heists and clever escapes.
  • 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_69ad85b2fed48190948c8765e453d270 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb3af0cc81909e575828caeaeae0 completed March 8, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69b36810958c81908982e0ef996dc480 completed March 13, 2026, 1:27 a.m.
NEDg Description generation batch_69b368b4e504819094ca0adbdbe7bfd9 completed March 13, 2026, 1:30 a.m.
NED2 Entity disambiguation (via description) batch_69b3693a8d6481909dadce4ac6109ff3 completed March 13, 2026, 1:32 a.m.
Created at: March 8, 2026, 3:17 p.m.