Triple

T3317209
Position Surface form Disambiguated ID Type / Status
Subject SMS Derfflinger E69709 entity
Predicate armorBeltMax P38465 FINISHED
Object up to 300 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: up to 300 mm | Statement: [SMS Derfflinger, armorBeltMax, up to 300 mm]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: armorBeltMax
Context triple: [SMS Derfflinger, armorBeltMax, up to 300 mm]
  • A. armorBelt
    Indicates that an entity is equipped with or wearing an armor belt as part of its protective gear.
  • B. armourBelt
    Indicates a relationship where an armour belt is equipped on, attached to, or associated with an entity (such as a character, vehicle, or structure) as protective gear.
  • C. armoredBeltThickness chosen
    Indicates the thickness of an entity’s protective armored belt in the context of its defensive structure or design.
  • D. armorType
    Indicates the specific category or classification of protective armor associated with an entity.
  • E. armorThicknessMax
    Indicates the maximum thickness of armor that an entity possesses or can withstand.
  • 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_69ad85a0bb048190a5458d2738012d61 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb11230b881908f5b554323729cc5 completed March 8, 2026, 5:25 p.m.
PD Predicate disambiguation batch_69ada4282730819092aa39c5f9269df0 completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:11 p.m.