Triple

T5846826
Position Surface form Disambiguated ID Type / Status
Subject Southeastern Iranian languages E129731 entity
Predicate hasNotableLanguage P7390 FINISHED
Object Munji E230686 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: Munji | Statement: [Southeastern Iranian languages, hasNotableLanguage, Munji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munji
Context triple: [Southeastern Iranian languages, hasNotableLanguage, Munji]
  • A. Munji chosen
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • B. Tanaeang
    Tanaeang is a village settlement located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
  • C. Junggumun
    Junggumun is a historical writing system used in Korea that incorporated Chinese characters to represent Korean grammatical elements and sounds.
  • D. Gukmun
    Gukmun is an old Korean term referring to the native Korean writing system that later came to be known as Joseongeul or Hangul.
  • E. Wiryeseong
    Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0351157508190a78d2a7141e0cee8 completed March 22, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0bfd6cffc8190b65252f02055e89c completed March 23, 2026, 4:21 a.m.
Created at: March 22, 2026, 3:55 p.m.