Triple

T1515922
Position Surface form Disambiguated ID Type / Status
Subject Ljubljana E32117 entity
Predicate officialLanguage P236 FINISHED
Object Slovene E28855 NE 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: Slovene | Statement: [Ljubljana, officialLanguage, Slovene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slovene
Context triple: [Ljubljana, officialLanguage, Slovene]
  • A. Slovene chosen
    Slovene is a South Slavic language spoken primarily in Slovenia and recognized as one of the official languages of the European Union.
  • B. Croatian
    Croatian is a South Slavic language primarily spoken in Croatia and recognized as one of the official languages of the European Union.
  • C. Triestine Venetian dialect
    The Triestine Venetian dialect is a regional variety of the Venetian language spoken in and around Trieste, characterized by a blend of Venetian, Slovene, German, and local linguistic influences.
  • D. Fran Ramovš Institute of the Slovenian Language
    The Fran Ramovš Institute of the Slovenian Language is a leading research institution dedicated to the study, standardization, and development of the Slovene language.
  • E. Slovak language
    The Slovak language is a West Slavic language spoken primarily in Slovakia and closely related to Czech and Polish.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a885e8caf88190a5fbb6159ce87786 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f688148190bcc7c14372ce5bd1 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad23429f1c81909f435030de687675 completed March 8, 2026, 7:20 a.m.
Created at: March 4, 2026, 7:26 p.m.