Triple

T16075464
Position Surface form Disambiguated ID Type / Status
Subject KV17 E389968 entity
Predicate hasDamageType P92407 FINISHED
Object structural cracking 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: structural cracking | Statement: [KV17, hasDamageType, structural cracking]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDamageType
Context triple: [KV17, hasDamageType, structural cracking]
  • A. hasTypeOfDamage chosen
    Indicates that an entity experiences or exhibits a specific kind or category of damage.
  • B. coversDamageType
    Indicates that one entity provides protection, compensation, or applicability for a specified type of damage.
  • C. hasCombatType
    Indicates that an entity is associated with a particular mode or category of combat it uses or participates in.
  • D. primaryDamageType
    Indicates the main kind of harm or injury that an action, event, or object is responsible for causing.
  • E. hasTypeOfEffect
    Indicates that one entity produces, exhibits, or is associated with a particular kind or category of effect on another entity or context.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1ff63edb0819092cbb671967bbdcd completed April 17, 2026, 9:37 a.m.
PD Predicate disambiguation batch_69e1827ad7c88190b867da511cbfb7fa completed April 17, 2026, 12:44 a.m.
Created at: April 10, 2026, 4:57 a.m.