Triple

T38588719
Position Surface form Disambiguated ID Type / Status
Subject Lord Marrowgar E932403 entity
Predicate secondaryDamageType P201304 FINISHED
Object frost 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: frost | Statement: [Lord Marrowgar, secondaryDamageType, frost]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: secondaryDamageType
Context triple: [Lord Marrowgar, secondaryDamageType, frost]
  • A. secondaryDamageSchool
    Indicates that a school experiences indirect or collateral damage as a consequence of another primary damaging event.
  • B. secondaryDam
    Indicates that an entity functions as a secondary or auxiliary dam in relation to a primary dam or water control structure.
  • C. primaryDamageType
    Indicates the main kind of harm or injury that an action, event, or object is responsible for causing.
  • D. secondaryHazardType
    Indicates the type or category of a hazard that occurs as a secondary or consequential effect of a primary hazard or event.
  • E. secondaryFire
    Indicates the use or activation of an alternate or secondary mode of firing in a weapon or tool, distinct from its primary fire action.
  • 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_69f76ec654d48190b421111cf26e54d9 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69ffe6e2eb688190a45fd2c6415cd86a completed May 10, 2026, 2:01 a.m.
PD Predicate disambiguation batch_69ffe65939488190a35b9c2e9c7ad868 completed May 10, 2026, 1:58 a.m.
PDg Predicate description generation batch_69ffe6e21f748190a18dfe0878d397f7 completed May 10, 2026, 2:01 a.m.
Created at: May 3, 2026, 4:32 p.m.