Triple

T18005225
Position Surface form Disambiguated ID Type / Status
Subject Ministerstwo Obrony Narodowej E430728 entity
Predicate shortName P43 FINISHED
Object MON NE NERFINISHED

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: [Ministerstwo Obrony Narodowej, shortName, MON]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MON
Context triple: [Ministerstwo Obrony Narodowej, shortName, MON]
  • A. MON
    MON is the standard abbreviation used for the Montreal Canadiens, the historic National Hockey League team based in Montreal, Quebec.
  • B. MON chosen
    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.
  • C. MON
    MON is the three-letter International Olympic Committee country code representing Monaco in Olympic competitions.
  • D. MON
    MON is the post-nominal abbreviation used to denote recipients of Nigeria’s national honor, the Order of the Niger.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b51ba1888190a339d726e92f376b completed April 19, 2026, 10:57 a.m.
Created at: April 10, 2026, 10:24 a.m.