Triple

T13154095
Position Surface form Disambiguated ID Type / Status
Subject Katharine of Bohemia E312538 entity
Predicate givenName P17 FINISHED
Object Katharine
Katharine is a feminine given name of Greek origin, commonly used in various forms across Europe and the English-speaking world.
 E1025931 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: Katharine | Statement: [Katharine of Bohemia, givenName, Katharine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Katharine
Context triple: [Katharine of Bohemia, givenName, Katharine]
  • A. Katherine
    Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
  • B. Katherine
    Katherine is one of the witty noblewomen in William Shakespeare’s comedy "Love’s Labour’s Lost," known for her sharp dialogue and role in the play’s romantic entanglements.
  • C. Katherine
    Katherine is the daughter of Evelyn Mulwray in the 1974 film noir "Chinatown," whose parentage is central to the movie's mystery and emotional impact.
  • D. Katherine
    Katherine is the mother of Thomasin.
  • E. Katherine
    Katherine is the central protagonist of the story "The Well," around whom the narrative’s main events and conflicts revolve.
  • 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: Katharine
Triple: [Katharine of Bohemia, givenName, Katharine]
Generated description
Katharine is a feminine given name of Greek origin, commonly used in various forms across Europe and the English-speaking world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Katharine
Target entity description: Katharine is a feminine given name of Greek origin, commonly used in various forms across Europe and the English-speaking world.
  • A. Katherine
    Katherine is a regional town in Australia's Northern Territory, known as a key service and transport hub near Nitmiluk (Katherine Gorge) National Park.
  • B. Katherine
    Katherine is the mother of Thomasin.
  • C. Katherine
    Katherine is one of the witty noblewomen in William Shakespeare’s comedy "Love’s Labour’s Lost," known for her sharp dialogue and role in the play’s romantic entanglements.
  • D. Katherine
    Katherine is the daughter of Evelyn Mulwray in the 1974 film noir "Chinatown," whose parentage is central to the movie's mystery and emotional impact.
  • E. Katherine
    Katherine is the central protagonist of the story "The Well," around whom the narrative’s main events and conflicts revolve.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c06ccb881909390df18e1a6f7ed completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5df07ec8190be64ed80d7e220b7 completed May 3, 2026, 7:14 a.m.
NEDg Description generation batch_69f6f694f8c48190adce4cddbf63777f completed May 3, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_69f6f7d8bfa0819097b3d9175bc56933 completed May 3, 2026, 7:23 a.m.
Created at: April 9, 2026, 9:11 p.m.