Triple

T968704
Position Surface form Disambiguated ID Type / Status
Subject The Robber Bride E20896 entity
Predicate mainCharacter P1183 FINISHED
Object Tony
Tony is one of the central protagonists in Margaret Atwood’s novel "The Robber Bride," known for her intellectual, introspective nature and complex relationships with the other main characters.
 E118947 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: Tony | Statement: [The Robber Bride, mainCharacter, Tony]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tony
Context triple: [The Robber Bride, mainCharacter, Tony]
  • A. Tony
    The Tony is a prestigious American theater award presented annually to recognize excellence in Broadway productions.
  • B. Ted
    Ted is a masculine given name, often a diminutive of Theodore or Edward, commonly used in English-speaking countries.
  • C. Ted
    Ted is a 2012 comedy film about a foul-mouthed living teddy bear, created by and starring Seth MacFarlane.
  • D. Tim
    Tim is the given name of Tim Wu, a prominent legal scholar and policy advocate known for coining the term "net neutrality."
  • E. Todd
    Todd is the maiden surname of Mary Todd Lincoln, the First Lady of the United States during Abraham Lincoln’s presidency.
  • 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: Tony
Triple: [The Robber Bride, mainCharacter, Tony]
Generated description
Tony is one of the central protagonists in Margaret Atwood’s novel "The Robber Bride," known for her intellectual, introspective nature and complex relationships with the other main characters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tony
Target entity description: Tony is one of the central protagonists in Margaret Atwood’s novel "The Robber Bride," known for her intellectual, introspective nature and complex relationships with the other main characters.
  • A. Tony
    The Tony is a prestigious American theater award presented annually to recognize excellence in Broadway productions.
  • B. Ted
    Ted is a masculine given name, often a diminutive of Theodore or Edward, commonly used in English-speaking countries.
  • C. Ted
    Ted is a 2012 comedy film about a foul-mouthed living teddy bear, created by and starring Seth MacFarlane.
  • D. Tim
    Tim is the given name of Tim Wu, a prominent legal scholar and policy advocate known for coining the term "net neutrality."
  • E. Todd
    Todd is the maiden surname of Mary Todd Lincoln, the First Lady of the United States during Abraham Lincoln’s presidency.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b4481f508190adcf0a965a23862c completed March 1, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2a11e4148190bb18849c52c2ed9a completed March 7, 2026, 1:37 p.m.
NEDg Description generation batch_69ac366e1a488190a30cd2806615c334 completed March 7, 2026, 2:30 p.m.
NED2 Entity disambiguation (via description) batch_69ac38dd63008190b9bccd53be4583de completed March 7, 2026, 2:40 p.m.
Created at: March 1, 2026, 7:40 p.m.