Triple

T9119124
Position Surface form Disambiguated ID Type / Status
Subject Yamaloka E218799 entity
Predicate contrastedWith P278 FINISHED
Object Naraka E344091 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: Naraka | Statement: [Yamaloka, contrastedWith, Naraka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naraka
Context triple: [Yamaloka, contrastedWith, Naraka]
  • A. Naraka chosen
    Naraka is the concept of an underworld or hell in several Indian religions, where souls undergo punishment or purification after death.
  • B. Yama Jigoku
    Yama Jigoku is one of Beppu’s famous “hell” hot spring sites, known for its boiling, vividly colored pools and dramatic geothermal scenery.
  • C. Umi Jigoku
    Umi Jigoku is one of Beppu’s famous “hell” hot springs in Japan, known for its striking cobalt-blue boiling water and scenic, geothermal landscape.
  • D. Dahāk
    Dahāk is an alternative name for Zahhak, the monstrous tyrant from Persian mythology and literature who is often depicted with serpents growing from his shoulders.
  • E. Oniishibozu Jigoku
    Oniishibozu Jigoku is one of Beppu’s famous “hell” hot spring sites, known for its bubbling, mud-like pools that resemble the shaved heads of Buddhist monks.
  • 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_69ca83dddd548190983b96c664f7f367 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8a7c6d48190a015efd17a017ca1 completed April 1, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0544c06ec8190917707d75db7e9c5 completed April 3, 2026, 11:59 p.m.
Created at: March 30, 2026, 7:17 p.m.