Triple

T5020183
Position Surface form Disambiguated ID Type / Status
Subject Llwynywermod E112830 entity
Predicate restorationEmphasized P38451 FINISHED
Object local materials 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: local materials | Statement: [Llwynywermod, restorationEmphasized, local materials]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: restorationEmphasized
Context triple: [Llwynywermod, restorationEmphasized, local materials]
  • A. restorationFocus chosen
    Indicates that the primary attention or effort is directed toward repairing, renewing, or returning something to a previous or improved state.
  • B. significantRestoration
    Indicates that an entity has undergone a major or substantial restoration effort that notably improves or returns it to a previous condition.
  • C. restored
    Indicates that an entity has returned another entity to a previous or improved state, condition, or position after damage, loss, or alteration.
  • D. restorationGoal
    Indicates that an action or plan is intended to return something to a previous, original, or improved state or condition.
  • E. restorationMeasure
    Indicates that an action or intervention is undertaken to repair, rehabilitate, or return something to a previous or improved 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_69bd4435c2f48190be593158cbfcf8a3 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7342c62881909acb35849da8761c completed March 20, 2026, 4:18 p.m.
PD Predicate disambiguation batch_69bd714ecfe08190b5830cfc1c74fa17 completed March 20, 2026, 4:09 p.m.
Created at: March 20, 2026, 1:36 p.m.