Triple

T9051772
Position Surface form Disambiguated ID Type / Status
Subject Mon language E216899 entity
Predicate glottologName P6521 FINISHED
Object Mon E56034 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: Mon | Statement: [Mon language, glottologName, Mon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mon
Context triple: [Mon language, glottologName, Mon]
  • A. Mon
    Mon is a town in the northeastern Indian state of Nagaland, known as the headquarters of Mon district and as a cultural center of the Konyak Naga tribe.
  • B. Mon chosen
    The Mon are one of the oldest ethnic groups in mainland Southeast Asia, historically influential in the spread of Theravada Buddhism and early state formation in what is now Myanmar and Thailand.
  • C. mon
    A mon is a traditional Japanese heraldic emblem used to represent individuals, families, clans, or institutions.
  • D. MON
    MON is the standard abbreviation used for the Montreal Canadiens, the historic National Hockey League team based in Montreal, Quebec.
  • E. MON
    MON is the commonly used abbreviation for Poland’s Ministry of National Defence, the government body responsible for the country’s defense policy and armed forces.
  • 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_69ca83d362e88190ae44b4e4dc194209 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc7a700de48190aa9f61d850e01cbd completed April 1, 2026, 1:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfebc90bf88190bbcdab07ca93f569 completed April 3, 2026, 4:33 p.m.
Created at: March 30, 2026, 7:10 p.m.