Triple

T14702530
Position Surface form Disambiguated ID Type / Status
Subject Tatjana E345340 entity
Predicate languageOfUse P237 FINISHED
Object Lithuanian E28856 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: Lithuanian | Statement: [Tatjana, languageOfUse, Lithuanian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lithuanian
Context triple: [Tatjana, languageOfUse, Lithuanian]
  • A. Lithuanian chosen
    Lithuanian is a Baltic language spoken primarily in Lithuania and known for preserving many archaic features of Proto-Indo-European.
  • B. Latuvi
    Latuvi is a small rural village in the Sierra Norte region of Oaxaca, Mexico, known for its mountainous landscapes and traditional indigenous culture.
  • C. Lithuanians
    Lithuanians are a Baltic ethnic group native to Lithuania, known for their distinct Indo-European language and cultural heritage in northeastern Europe.
  • D. Latgalian
    Latgalian is an Eastern Baltic language variety closely related to Latvian, traditionally spoken by the Latgalian ethnic group in the Latgale region of eastern Latvia.
  • E. Varaždin Kajkavian
    Varaždin Kajkavian is a regional variety of the Kajkavian dialect spoken in and around the city of Varaždin in northern Croatia, characterized by distinctive phonological and lexical features.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb6071e5c8190bb5509c859135c2d completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0861c308190af0b5da403ecb321 completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:28 a.m.