Triple

T15001150
Position Surface form Disambiguated ID Type / Status
Subject Tuka trial of 1929 E374091 entity
Predicate hasDefendantEthnicity P29967 FINISHED
Object Slovak 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: Slovak | Statement: [Tuka trial of 1929, hasDefendantEthnicity, Slovak]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDefendantEthnicity
Context triple: [Tuka trial of 1929, hasDefendantEthnicity, Slovak]
  • A. defendantsNationality chosen
    Indicates that the specified nationality is attributed to the defendants in a legal case.
  • B. holderEthnicity
    Indicates the ethnic background or group to which the holder of something (e.g., a document, account, or item) belongs.
  • C. hasEthnicCharacteristic
    Indicates that an entity possesses or is associated with a particular ethnic characteristic or identity.
  • D. primaryPerpetratorEthnicity
    Indicates the ethnic group to which the main individual responsible for an act or incident belongs.
  • E. hasMainDefendant
    Indicates that a legal case or proceeding identifies a specific individual or entity as its primary defendant.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded72fec948190b1c9705538c57976 completed April 15, 2026, 12:09 a.m.
PD Predicate disambiguation batch_69de9a6531a88190acde65199a477350 completed April 14, 2026, 7:49 p.m.
Created at: April 10, 2026, 2:54 a.m.