Triple

T37662742
Position Surface form Disambiguated ID Type / Status
Subject Potion of Fire Resistance E937751 entity
Predicate effectAppliesTo P1129 FINISHED
Object fire damage 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: fire damage | Statement: [Potion of Fire Resistance, effectAppliesTo, fire damage]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: effectAppliesTo
Context triple: [Potion of Fire Resistance, effectAppliesTo, fire damage]
  • A. hasEffectIn
    Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
  • B. appliesTo chosen
    Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
  • C. appliesAt
    Indicates that an action, rule, or condition is relevant to or in effect at a specific location, context, or point in time.
  • D. appliesAlsoTo
    Indicates that a condition, rule, or characteristic that applies to one entity is additionally applicable to another entity.
  • E. appliesFrom
    Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
  • 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_69f76ed6df7c8190b018e5baea716ceb completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fe349879848190bcd77e3cc3470458 completed May 8, 2026, 7:08 p.m.
PD Predicate disambiguation batch_69fe31e3cf908190b23ebc2f7fe58722 completed May 8, 2026, 6:56 p.m.
Created at: May 3, 2026, 4:18 p.m.