Triple

T9119117
Position Surface form Disambiguated ID Type / Status
Subject Yamaloka E218799 entity
Predicate hasAlternativeName P39 FINISHED
Object Yama-loka 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: Yama-loka | Statement: [Yamaloka, hasAlternativeName, Yama-loka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yama-loka
Context triple: [Yamaloka, hasAlternativeName, Yama-loka]
  • A. 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.
  • B. Naraka chosen
    Naraka is the concept of an underworld or hell in several Indian religions, where souls undergo punishment or purification after death.
  • C. Yama
    Yama is the Hindu god of death and justice, traditionally regarded as the ruler of the afterlife and judge of the souls of the dead.
  • D. Yama
    Yama is the historical name of the Russian town now known as Kingisepp, located in Leningrad Oblast near the border with Estonia.
  • E. Yama
    Yama is a Linux Security Module that enhances process and ptrace-related security by restricting how processes can inspect or interfere with each other.
  • 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_69d0307c9f608190aad73bcf82ae334e completed April 3, 2026, 9:26 p.m.
Created at: March 30, 2026, 7:17 p.m.