Triple

T20354586
Position Surface form Disambiguated ID Type / Status
Subject Kishkindha E496107 entity
Predicate associatedCharacter P12208 FINISHED
Object Angada NE NERFINISHED

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: Angada | Statement: [Kishkindha, associatedCharacter, Angada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angada
Context triple: [Kishkindha, associatedCharacter, Angada]
  • A. Angada chosen
    Angada is a heroic Vanara prince in the Indian epic Ramayana, renowned for his loyalty to Rama and his role in the war against Ravana.
  • B. Kalahandi
    Kalahandi is a district in the Indian state of Odisha, known for its agrarian economy, tribal population, and history of both rich cultural heritage and severe drought-related poverty.
  • C. Nikaweratiya
    Nikaweratiya is a town in Sri Lanka’s North Western Province known for its agricultural surroundings and role as a local commercial center.
  • D. Tanguturi
    Tanguturi is the given name of T. Prakasam, a prominent Indian freedom fighter and former Chief Minister of the Madras Presidency and Andhra State.
  • E. Bhailsa
    Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a3f7f48190b37f354574028ca6 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67852ca9881908a5af18005639859 completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:25 a.m.