Triple

T13528787
Position Surface form Disambiguated ID Type / Status
Subject Kurs automatic docking system E323078 entity
Predicate backupControlMode P110701 FINISHED
Object manual via TORU 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: manual via TORU | Statement: [Kurs automatic docking system, backupControlMode, manual via TORU]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: backupControlMode
Context triple: [Kurs automatic docking system, backupControlMode, manual via TORU]
  • A. backupCommander
    Indicates that one entity serves as the designated backup or alternate commander for another entity.
  • B. backupScope
    Indicates the extent or range of data, resources, or components that are included in a backup operation.
  • C. backsUp
    Indicates that one entity provides support, reinforcement, or confirmation for another entity’s actions, statements, or position.
  • D. backupCommandModulePilot
    Indicates that an entity serves as the backup pilot for a command module in place of the primary pilot.
  • E. supportsBackupCopy
    Indicates that one entity provides the capability or functionality to create, maintain, or use a backup copy of another entity.
  • F. None of above. chosen

Provenance (4 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafb8e0cc8190b47f6aeb8ced470e completed April 12, 2026, 2:44 p.m.
PD Predicate disambiguation batch_69dbae1046c48190b4ee98c6c9cb9d85 completed April 12, 2026, 2:37 p.m.
PDg Predicate description generation batch_69dbaecc98cc8190829f5be759c4f1e3 completed April 12, 2026, 2:40 p.m.
Created at: April 9, 2026, 9:44 p.m.