Triple

T11363575
Position Surface form Disambiguated ID Type / Status
Subject Nagato class E269145 entity
Predicate gunCaliberMetric P6076 FINISHED
Object 410 mm LITERAL 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: 410 mm | Statement: [Nagato class, gunCaliberMetric, 410 mm]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: gunCaliberMetric
Context triple: [Nagato class, gunCaliberMetric, 410 mm]
  • A. gunCalibre chosen
    Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
  • B. natoCaliberClass
    Indicates that two ammunition types share the same standardized NATO caliber classification.
  • C. ammunitionType
    Indicates the specific kind or category of ammunition associated with or used by an entity.
  • D. barrelLengthInCalibers
    Indicates the length of a barrel expressed as a multiple of its bore diameter (in calibers), describing how many times the bore diameter fits into the barrel length.
  • E. ammunitionCapacity
    Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
  • F. None of above.

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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d800160a1c81909d115bf89fe54a49 completed April 9, 2026, 7:37 p.m.
PD Predicate disambiguation batch_69d7e7022d508190996f9be0847c2b41 completed April 9, 2026, 5:50 p.m.
Created at: April 8, 2026, 9:33 p.m.