Triple

T21931993
Position Surface form Disambiguated ID Type / Status
Subject Venusberg E541587 entity
Predicate hasCharacter P2308 FINISHED
Object Lucy
Lucy is a character in the medieval German legend of Venusberg, associated with the enchanted mountain realm of the goddess Venus.
E1509698 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: Lucy | Statement: [Venusberg, hasCharacter, Lucy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucy
Context triple: [Venusberg, hasCharacter, Lucy]
  • A. Lucy
    Lucy is a NASA Discovery Program space mission designed to study Jupiter’s Trojan asteroids to better understand the early solar system’s formation and evolution.
  • B. Lucy
    "Lucy" is a coming-of-age novella by Jamaica Kincaid that follows a young Caribbean woman navigating identity, colonial legacy, and independence while working as an au pair in the United States.
  • C. Lucy
    Lucy is a fictional character named in the context of "Loosies," likely serving as a supporting figure in that film’s narrative.
  • D. Lucy
    Lucy is a singer-songwriter and musician best known as a solo indie rock artist and as a member of the supergroup boygenius.
  • E. Lucy
    Lucy is the protagonist of the romance story "Kissing Lessons," around whom the central emotional and narrative developments 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: Lucy
Triple: [Venusberg, hasCharacter, Lucy]
Generated description
Lucy is a character in the medieval German legend of Venusberg, associated with the enchanted mountain realm of the goddess Venus.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lucy
Target entity description: Lucy is a character in the medieval German legend of Venusberg, associated with the enchanted mountain realm of the goddess Venus.
  • A. Lucy
    Lucy is a feminine given name of Latin origin meaning "light," commonly used in many English-speaking and European countries.
  • B. Lucy
    Lucy is a character portrayed by actress and filmmaker Alice Englert.
  • C. Lucy
    Lucy is the protagonist of the romance story "Kissing Lessons," around whom the central emotional and narrative developments revolve.
  • D. Lucy
    Lucy is a fictional girl who appears as one of Esperanza’s neighborhood friends in Sandra Cisneros’s coming-of-age novel *The House on Mango Street*.
  • E. Lucy
    Lucy is a fictional character from the British animated children's television series "Twin Town."
  • 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_69e0c47d74488190a15119108794a307 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f123ffde64819084a869d2d569718f completed April 28, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a60e636d0819082c3d81b051c9165 completed May 18, 2026, 12:44 a.m.
NEDg Description generation batch_6a0a61b197fc8190905c86e03c1cf5b9 completed May 18, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_6a0a6240a5008190a745a20a51d3f239 completed May 18, 2026, 12:50 a.m.
Created at: April 16, 2026, 7:47 p.m.