Triple

T28461287
Position Surface form Disambiguated ID Type / Status
Subject Kočevje E720160 entity
Predicate warHistory P160765 FINISHED
Object population changes during and after World War II 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: population changes during and after World War II | Statement: [Kočevje, warHistory, population changes during and after World War II]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: warHistory
Context triple: [Kočevje, warHistory, population changes during and after World War II]
  • A. worldWar
    Indicates a large-scale armed conflict involving multiple nations across different regions of the world, typically encompassing numerous battles, alliances, and theaters of war.
  • B. worldWarIService
    Indicates that an entity served or participated in military service during World War I.
  • C. militaryHistoryTopic
    Indicates that there exists a relationship where the subject is a topic, theme, or subject matter specifically concerned with military history.
  • D. postWarHistory chosen
    Indicates a relationship where something concerns, describes, or belongs to the historical period and events following a specific war.
  • E. majorWar
    Indicates a large-scale, intense armed conflict between major powers or involving substantial military forces and widespread impact.
  • 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_69f01a58a67c819097936d9e8da8d6e6 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64ea596448190bf7c3cf5f1220770 completed May 2, 2026, 7:21 p.m.
PD Predicate disambiguation batch_69f64caede108190a35cc7cbfead866f completed May 2, 2026, 7:12 p.m.
Created at: April 28, 2026, 2:40 a.m.