Triple

T2421518
Position Surface form Disambiguated ID Type / Status
Subject Japanese battleship Mutsu E53428 entity
Predicate mainBatteryCaliber P6076 FINISHED
Object 41 cm 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: 41 cm | Statement: [Japanese battleship Mutsu, mainBatteryCaliber, 41 cm]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mainBatteryCaliber
Context triple: [Japanese battleship Mutsu, mainBatteryCaliber, 41 cm]
  • A. gunCalibre chosen
    Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
  • B. ammunitionType
    Indicates the specific kind or category of ammunition associated with or used by an entity.
  • C. ammunitionCapacity
    Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
  • D. batteryType
    Indicates the specific kind or category of battery associated with or used by an entity.
  • E. hasBackupBattery
    Indicates that an entity is equipped with an additional battery intended to provide power when the primary power source is unavailable or fails.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc9f342e88190a430b02842ded418 completed March 7, 2026, 6:47 a.m.
PD Predicate disambiguation batch_69abc5a889948190b77de4ef6ac815a8 completed March 7, 2026, 6:28 a.m.
Created at: March 6, 2026, 9:42 p.m.