Triple

T8518459
Position Surface form Disambiguated ID Type / Status
Subject Mundari E201634 entity
Predicate hasDialect P4251 FINISHED
Object Naguri
Naguri is a regional dialect of the Mundari language spoken by Munda communities in eastern India.
 E827166 NE FINISHED

How this triple was built (4 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: Naguri | Statement: [Mundari, hasDialect, Naguri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Naguri
Context triple: [Mundari, hasDialect, Naguri]
  • A. Nuriro
    Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
  • B. Nōgata
    Nōgata is a city in western Japan located in Fukuoka Prefecture on the island of Kyushu.
  • C. Yonashiro
    Yonashiro was a former town in Okinawa Prefecture, Japan, that later became part of the city of Uruma through municipal merger.
  • D. Nagahori
    Nagahori is a district in Osaka, Japan, known primarily as an urban area served by the Osaka Metro Nagahori Tsurumi-ryokuchi Line.
  • E. Togoshi
    Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Naguri
Triple: [Mundari, hasDialect, Naguri]
Generated description
Naguri is a regional dialect of the Mundari language spoken by Munda communities in eastern India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Naguri
Target entity description: Naguri is a regional dialect of the Mundari language spoken by Munda communities in eastern India.
  • A. Nuriro
    Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
  • B. Nōgata
    Nōgata is a city in western Japan located in Fukuoka Prefecture on the island of Kyushu.
  • C. Yonashiro
    Yonashiro was a former town in Okinawa Prefecture, Japan, that later became part of the city of Uruma through municipal merger.
  • D. Nagahori
    Nagahori is a district in Osaka, Japan, known primarily as an urban area served by the Osaka Metro Nagahori Tsurumi-ryokuchi Line.
  • E. Togoshi
    Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
  • F. None of above. chosen

Provenance (5 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe626787c819087e72dd76b2d9310 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1ea9d96ac81908115489681070bcc completed April 5, 2026, 4:52 a.m.
NEDg Description generation batch_69d1eb79be388190853e0e7c29287294 completed April 5, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d1ebf0a99081908ae0c4bceadc42bc completed April 5, 2026, 4:58 a.m.
Created at: March 30, 2026, 6:16 p.m.