Triple

T8718319
Position Surface form Disambiguated ID Type / Status
Subject Eastern Hindi languages E206949 entity
Predicate hasMember P10 FINISHED
Object Surgujia E327859 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: Surgujia | Statement: [Eastern Hindi languages, hasMember, Surgujia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Surgujia
Context triple: [Eastern Hindi languages, hasMember, Surgujia]
  • A. Surgujia chosen
    Surgujia is a regional dialect of the Chhattisgarhi language spoken primarily in parts of the Indian state of Chhattisgarh.
  • B. Sikiajhora
    Sikiajhora is a forest stream and wetland area within West Bengal’s Buxa Tiger Reserve, known for its rich biodiversity and boat-based wildlife viewing.
  • C. Sarju
    Sarju is an alternate name for the Sarayu, a river historically associated with the ancient Indian city of Ayodhya and revered in Hindu tradition.
  • D. Kulisusu
    Kulisusu is a town and administrative center located in the province of Southeast Sulawesi, Indonesia.
  • E. Sorya
    Sorya is a regional dialect of the Kumaoni language spoken in parts of the Indian Himalayan region.
  • 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_69ca83572d4881909bef3be2b578d539 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5cdac6988190b9f9cc1f350aae53 completed March 31, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28ec7148819096f7fa33e4588b62 completed April 3, 2026, 2:41 a.m.
Created at: March 30, 2026, 6:36 p.m.