Triple

T4894859
Position Surface form Disambiguated ID Type / Status
Subject MOD E109651 entity
Predicate usesAbbreviation P43 FINISHED
Object MOD unclear NED1 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: MOD | Statement: [MOD, usesAbbreviation, MOD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MOD
Context triple: [MOD, usesAbbreviation, MOD]
  • A. MOD
    MOD is the commonly used abbreviation for Japan’s Ministry of Defense, the government body responsible for the country’s national defense and Self-Defense Forces.
  • B. MOD
    MOD is the commonly used abbreviation for the United Kingdom’s Ministry of Defence, the government department responsible for implementing defense policy and overseeing the armed forces.
  • C. MODS
    MODS (Metadata Object Description Schema) is a bibliographic metadata standard developed by the Library of Congress that provides a rich, XML-based format for describing digital and print resources.
  • D. Modau
    The Modau is a small river in the German state of Hesse that flows through the city of Darmstadt before joining the Rhine.
  • E. MOB
    MOB is the three-letter IATA airport code for Mobile Regional Airport in Mobile, Alabama, United States.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e27cdf48190bb9bd13bd25b887e completed March 20, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fc665e08190ae067746d6c19018 completed March 21, 2026, 10:15 a.m.
Created at: March 20, 2026, 1:28 p.m.