Triple

T1061229
Position Surface form Disambiguated ID Type / Status
Subject The Witty Fair One E22910 entity
Predicate hasCharacter P2308 FINISHED
Object Clare
Clare is a central character in the Restoration comedy "The Witty Fair One," known for embodying the play’s themes of wit, romance, and social intrigue.
E126371 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: Clare | Statement: [The Witty Fair One, hasCharacter, Clare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clare
Context triple: [The Witty Fair One, hasCharacter, Clare]
  • A. Clare West
    Clare West was an early Hollywood costume designer known for her influential work on major silent films, including collaborations with director Cecil B. DeMille.
  • B. Bethany
    Bethany is a village near Jerusalem mentioned in the New Testament, traditionally known as the home of Mary, Martha, and Lazarus and a frequent place visited by Jesus.
  • C. Ennis
    Ennis is a small Texas city known for its historic downtown, annual Bluebonnet Trails Festival, and location along major transportation routes south of Dallas.
  • D. Menstrie
    Menstrie is a small village in central Scotland, situated at the foot of the Ochil Hills in Clackmannanshire.
  • E. Frances
    Frances is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • 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: Clare
Triple: [The Witty Fair One, hasCharacter, Clare]
Generated description
Clare is a central character in the Restoration comedy "The Witty Fair One," known for embodying the play’s themes of wit, romance, and social intrigue.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Clare
Target entity description: Clare is a central character in the Restoration comedy "The Witty Fair One," known for embodying the play’s themes of wit, romance, and social intrigue.
  • A. Clare West
    Clare West was an early Hollywood costume designer known for her influential work on major silent films, including collaborations with director Cecil B. DeMille.
  • B. Bethany
    Bethany is a village near Jerusalem mentioned in the New Testament, traditionally known as the home of Mary, Martha, and Lazarus and a frequent place visited by Jesus.
  • C. Ennis
    Ennis is a small Texas city known for its historic downtown, annual Bluebonnet Trails Festival, and location along major transportation routes south of Dallas.
  • D. Menstrie
    Menstrie is a small village in central Scotland, situated at the foot of the Ochil Hills in Clackmannanshire.
  • E. Frances
    Frances is a feminine given name of Latin origin, commonly used in English-speaking countries.
  • 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_69a493dada0481909c43649f9843ea91 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8f531f481909a40558811379992 completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c1d82c88190b418e2e2f050b563 completed March 7, 2026, 4:02 p.m.
NEDg Description generation batch_69ac4e109c3c8190abcbc66aef59c52f completed March 7, 2026, 4:10 p.m.
NED2 Entity disambiguation (via description) batch_69ac4e646698819083403336eb07b7ff completed March 7, 2026, 4:12 p.m.
Created at: March 1, 2026, 7:42 p.m.