Triple

T15609513
Position Surface form Disambiguated ID Type / Status
Subject Lepenica E375250 entity
Predicate tributaryOf P415 FINISHED
Object Velika Morava E76777 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: Velika Morava | Statement: [Lepenica, tributaryOf, Velika Morava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velika Morava
Context triple: [Lepenica, tributaryOf, Velika Morava]
  • A. Velika Morava chosen
    Velika Morava is a major river in central Serbia formed by the confluence of the West and South Morava, flowing northward before joining the Danube.
  • B. Vukosava
    Vukosava is known in Serbian medieval history as the mother of Saint Prince Lazar, the revered ruler and martyr of the Battle of Kosovo.
  • C. Morava River
    The Morava River is a major Central European river flowing through the Czech Republic, Slovakia, and Austria, forming part of the natural border between the latter two countries before joining the Danube.
  • D. Morava River
    The Morava River is a major river system in Serbia that flows through the central part of the country and serves as an important natural and economic corridor.
  • E. Mayo-Sava
    Mayo-Sava is an administrative department in Cameroon's Far North Region, known for its diverse ethnic communities and proximity to the Nigerian border.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e8024948190a6c711f2e5c2aac4 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00a502c82881908d5b6f7c23e8a403 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 4:13 a.m.