Triple

T21908355
Position Surface form Disambiguated ID Type / Status
Subject Cāndra school E540997 entity
Predicate namedAfter P63 FINISHED
Object Candra
Candra is a figure after whom the Cāndra school of Sanskrit grammar is named, indicating his role as an influential grammarian or scholar in that tradition.
E1508196 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: Candra | Statement: [Cāndra school, namedAfter, Candra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Candra
Context triple: [Cāndra school, namedAfter, Candra]
  • A. Selene
    Selene is the tourist lunar excursion vehicle featured in Arthur C. Clarke’s science fiction novel "A Fall of Moondust."
  • B. Selene
    Selene is the Greek goddess and personification of the Moon, often depicted driving a silver chariot across the night sky.
  • C. Selene
    Selene is a powerful and ancient mutant sorceress in Marvel Comics, often portrayed as a vampiric villain and prominent member of the Hellfire Club.
  • D. Rahu
    Rahu is a shadowy celestial deity in Hindu astrology and mythology, associated with eclipses, karmic obstacles, and one of the nine planetary influences (Navagraha).
  • E. Luna
    Luna is a Spanish surname most prominently associated with Mexican actor and filmmaker Diego Luna.
  • 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: Candra
Triple: [Cāndra school, namedAfter, Candra]
Generated description
Candra is a figure after whom the Cāndra school of Sanskrit grammar is named, indicating his role as an influential grammarian or scholar in that tradition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Candra
Target entity description: Candra is a figure after whom the Cāndra school of Sanskrit grammar is named, indicating his role as an influential grammarian or scholar in that tradition.
  • A. Selene
    Selene is the tourist lunar excursion vehicle featured in Arthur C. Clarke’s science fiction novel "A Fall of Moondust."
  • B. Selene
    Selene is the Greek goddess and personification of the Moon, often depicted driving a silver chariot across the night sky.
  • C. Selene
    Selene is a powerful and ancient mutant sorceress in Marvel Comics, often portrayed as a vampiric villain and prominent member of the Hellfire Club.
  • D. Rahu
    Rahu is a shadowy celestial deity in Hindu astrology and mythology, associated with eclipses, karmic obstacles, and one of the nine planetary influences (Navagraha).
  • E. Luna
    Luna is the protagonist of the game "Lunar: The Silver Star," a classic Japanese role-playing game known for its character-driven story and fantasy adventure.
  • 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f121d806688190b23502aacbfde4bd completed April 28, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a5a0b1d188190a97a8b92cefcf340 completed May 18, 2026, 12:15 a.m.
NEDg Description generation batch_6a0a5c11dc7c819083658351bbf76fa8 completed May 18, 2026, 12:23 a.m.
NED2 Entity disambiguation (via description) batch_6a0a5cf6ede48190a55392a985a73896 completed May 18, 2026, 12:27 a.m.
Created at: April 16, 2026, 7:39 p.m.