Triple

T260319
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Howe E5526 entity
Predicate familyName P18 FINISHED
Object Howe
Howe is an English-language surname of Anglo-Norman and Old English origin, borne by numerous notable figures across politics, the military, the arts, and sports.
 E34373 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: Howe | Statement: [Elizabeth Howe, familyName, Howe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Howe
Context triple: [Elizabeth Howe, familyName, Howe]
  • A. Trent
    The Trent is one of the principal rivers in England, flowing through the Midlands and joining the Humber estuary before reaching the North Sea.
  • B. Frick
    Frick is a surname most prominently associated with American industrialist and art patron Henry Clay Frick.
  • C. Guilfoyle
    Guilfoyle is a surname most prominently associated in contemporary American culture with television personality and political figure Kimberly Guilfoyle.
  • D. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • E. Nelson
    Nelson is a common English-language surname borne by numerous notable figures across politics, sports, entertainment, and academia.
  • 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: Howe
Triple: [Elizabeth Howe, familyName, Howe]
Generated description
Howe is an English-language surname of Anglo-Norman and Old English origin, borne by numerous notable figures across politics, the military, the arts, and sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Howe
Target entity description: Howe is an English-language surname of Anglo-Norman and Old English origin, borne by numerous notable figures across politics, the military, the arts, and sports.
  • A. Trent
    The Trent is one of the principal rivers in England, flowing through the Midlands and joining the Humber estuary before reaching the North Sea.
  • B. Frick
    Frick is a surname most prominently associated with American industrialist and art patron Henry Clay Frick.
  • C. Guilfoyle
    Guilfoyle is a surname most prominently associated in contemporary American culture with television personality and political figure Kimberly Guilfoyle.
  • D. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • E. Nelson
    Nelson is a common English-language surname borne by numerous notable figures across politics, sports, entertainment, and academia.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d72dad4819092c9502e6e4edc44 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a389ab230c8190982eead1ef7b5c75 completed March 1, 2026, 12:34 a.m.
NEDg Description generation batch_69a38a0114b481908c9363e926b4b3ae completed March 1, 2026, 12:36 a.m.
NED2 Entity disambiguation (via description) batch_69a38a699a6081908c167ce9ad55a660 completed March 1, 2026, 12:38 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.