Triple

T836785
Position Surface form Disambiguated ID Type / Status
Subject The Corsair E18085 entity
Predicate featuresCharacter P626 FINISHED
Object Medora
Medora is the courageous and devoted heroine of Lord Byron’s narrative poem "The Corsair," often depicted as the pirate Conrad’s beloved.
 E114331 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: Medora | Statement: [The Corsair, featuresCharacter, Medora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Medora
Context triple: [The Corsair, featuresCharacter, Medora]
  • A. Kanesville
    Kanesville was the mid-19th-century Mormon settlement that later became the city of Council Bluffs, Iowa.
  • B. Harpley
    Harpley is a small rural village in Norfolk, England, known for its traditional English countryside setting and historic parish church.
  • C. Elk Point, South Dakota
    Elk Point, South Dakota is a small city in southeastern South Dakota known as one of the state’s oldest settlements and a local hub for the surrounding agricultural region.
  • D. Hutchinson
    Hutchinson is a common English surname borne by numerous notable individuals across fields such as science, politics, and the arts.
  • E. Beresford, South Dakota
    Beresford, South Dakota is a small city in southeastern South Dakota known for its agricultural roots and tight-knit rural community.
  • 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: Medora
Triple: [The Corsair, featuresCharacter, Medora]
Generated description
Medora is the courageous and devoted heroine of Lord Byron’s narrative poem "The Corsair," often depicted as the pirate Conrad’s beloved.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Medora
Target entity description: Medora is the courageous and devoted heroine of Lord Byron’s narrative poem "The Corsair," often depicted as the pirate Conrad’s beloved.
  • A. Kanesville
    Kanesville was the mid-19th-century Mormon settlement that later became the city of Council Bluffs, Iowa.
  • B. Harpley
    Harpley is a small rural village in Norfolk, England, known for its traditional English countryside setting and historic parish church.
  • C. Elk Point, South Dakota
    Elk Point, South Dakota is a small city in southeastern South Dakota known as one of the state’s oldest settlements and a local hub for the surrounding agricultural region.
  • D. Hutchinson
    Hutchinson is a common English surname borne by numerous notable individuals across fields such as science, politics, and the arts.
  • E. Beresford, South Dakota
    Beresford, South Dakota is a small city in southeastern South Dakota known for its agricultural roots and tight-knit rural community.
  • 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_69a49389f44881909a608fb27d89f247 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abcf69888190b342363978273ae2 completed March 1, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16f749dc819097231c0becb4150b completed March 7, 2026, 12:15 p.m.
NEDg Description generation batch_69ac1778cf0081908f520c40c4282633 completed March 7, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_69ac181f732c819093612c684d9fcbfd completed March 7, 2026, 12:20 p.m.
Created at: March 1, 2026, 7:38 p.m.