Triple

T4692593
Position Surface form Disambiguated ID Type / Status
Subject Lisbon’s royal archives E104068 entity
Predicate resultOfDestruction P53688 FINISHED
Object loss of large quantities of historical records 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: loss of large quantities of historical records | Statement: [Lisbon’s royal archives, resultOfDestruction, loss of large quantities of historical records]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: resultOfDestruction
Context triple: [Lisbon’s royal archives, resultOfDestruction, loss of large quantities of historical records]
  • A. typeOfDestruction
    Indicates the specific manner or method by which something is destroyed or caused to cease to exist.
  • B. sufferedDestructionOf
    Indicates that one entity experienced damage, ruin, or loss as a result of the destruction of another entity.
  • C. consequenceOfDestruction chosen
    Indicates that one event, state, or condition occurs as a direct result of a prior act of destruction.
  • D. hasCauseOfDestruction
    Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
  • E. destroyedDuring
    Indicates that one entity was destroyed in the course of, or as a consequence of, a specified event or time period.
  • 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_69bd43df91f481908e9add1b617b60ef completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd66059bfc8190885d26d05dd38df1 completed March 20, 2026, 3:21 p.m.
PD Predicate disambiguation batch_69bd6219da948190bbbb50f08573ab4d completed March 20, 2026, 3:04 p.m.
Created at: March 20, 2026, 1:16 p.m.