Triple

T6367141
Position Surface form Disambiguated ID Type / Status
Subject Mongol Empire E143254 entity
Predicate legalSystem P605 FINISHED
Object Yassa E334619 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: Yassa | Statement: [Mongol Empire, legalSystem, Yassa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yassa
Context triple: [Mongol Empire, legalSystem, Yassa]
  • A. Yassa chosen
    Yassa was the codified legal and administrative code traditionally attributed to Genghis Khan that governed the Mongol Empire and its successor states.
  • B. Kandia
    Kandia is a remote valley and settlement area located within Pakistan’s Kohistan mountain ranges, known for its rugged terrain and isolated communities.
  • C. Iéna
    Iéna is a Paris Métro station in the 16th arrondissement, located near landmarks such as the Palais de Tokyo and the Trocadéro.
  • D. Ngola
    Ngola is an alternative name for the Angolar people, a community of African descent primarily associated with São Tomé and Príncipe.
  • E. Ndiass
    Ndiass is a village in western Senegal that serves as the host community for Blaise Diagne International Airport, one of the country’s main air transport hubs.
  • 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_69c008d8c61081908bcaf61510d881ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06811de2881909ead116117956981 completed March 22, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6386f361c819098dbe01b0cb07b06 completed March 27, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:32 p.m.