Triple

T8559668
Position Surface form Disambiguated ID Type / Status
Subject Yamuna E202658 entity
Predicate parents P7318 FINISHED
Object Sanjna E218802 NE FINISHED

How this triple was built (2 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: Sanjna | Statement: [Yamuna, parents, Sanjna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sanjna
Context triple: [Yamuna, parents, Sanjna]
  • A. Sanjna chosen
    Sanjna is a figure in Hindu mythology known as the wife of the sun god Surya and the daughter of the god of justice, often associated with themes of devotion and transformation.
  • B. Anjali
    Anjali is an Indian pediatrician best known as the wife of legendary cricketer Sachin Tendulkar.
  • C. Madhavi
    Madhavi is a celebrated courtesan and pivotal literary figure in ancient Tamil epic tradition, prominently featured in the Sangam-era works Silappatikaram and its sequel Manimekalai.
  • D. Aditi
    Aditi is a Vedic mother goddess in Hindu mythology, revered as the personification of boundlessness and the mother of many deities.
  • E. Aparna
    Aparna is a central character in Satyajit Ray’s film "Apur Sansar," portrayed as Apu’s wife whose relationship with him profoundly shapes the emotional core of the story.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe949974c8190a75d9c767ca5fa5a completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea871dd3081908e24c4d1c60a8381 completed April 2, 2026, 5:33 p.m.
Created at: March 30, 2026, 6:20 p.m.