Triple

T6944543
Position Surface form Disambiguated ID Type / Status
Subject The Graveyard Book E160761 entity
Predicate hasCharacter P2308 FINISHED
Object Miss Lupescu
Miss Lupescu is a strict but caring werewolf and guardian figure who helps protect and educate the protagonist, Bod, in Neil Gaiman’s novel "The Graveyard Book."
 E631637 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: Miss Lupescu | Statement: [The Graveyard Book, hasCharacter, Miss Lupescu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Miss Lupescu
Context triple: [The Graveyard Book, hasCharacter, Miss Lupescu]
  • A. Maria Sursuvul
    Maria Sursuvul was a Bulgarian noblewoman of the early medieval period, best known as the mother of Tsar Peter I of Bulgaria.
  • B. Lucia
    Lucia is a feminine given name of Latin origin, commonly associated with light and used in various European cultures.
  • C. Corina
    Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
  • D. Stefania
    Stefania is a feminine given name of Italian origin, commonly used in Italy and other European countries.
  • E. Rosalinda
    Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
  • 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: Miss Lupescu
Triple: [The Graveyard Book, hasCharacter, Miss Lupescu]
Generated description
Miss Lupescu is a strict but caring werewolf and guardian figure who helps protect and educate the protagonist, Bod, in Neil Gaiman’s novel "The Graveyard Book."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Miss Lupescu
Target entity description: Miss Lupescu is a strict but caring werewolf and guardian figure who helps protect and educate the protagonist, Bod, in Neil Gaiman’s novel "The Graveyard Book."
  • A. Maria Sursuvul
    Maria Sursuvul was a Bulgarian noblewoman of the early medieval period, best known as the mother of Tsar Peter I of Bulgaria.
  • B. Lucia
    Lucia is a feminine given name of Latin origin, commonly associated with light and used in various European cultures.
  • C. Corina
    Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
  • D. Stefania
    Stefania is a feminine given name of Italian origin, commonly used in Italy and other European countries.
  • E. Rosalinda
    Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
  • 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_69c6884f3db4819080ad65da69386206 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da88b79c8190a8f297dfc4972979 completed March 27, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75866a2408190b472fdad73a8799b completed March 28, 2026, 4:26 a.m.
NEDg Description generation batch_69c75a9485508190b65bb9447b0e3f69 completed March 28, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c75b0ec4088190a492faea485dd7d1 completed March 28, 2026, 4:37 a.m.
Created at: March 27, 2026, 2:28 p.m.