Triple

T4364041
Position Surface form Disambiguated ID Type / Status
Subject Römer E98727 entity
Predicate hasNearby P350 FINISHED
Object Main River E113003 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: Main River | Statement: [Römer, hasNearby, Main River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Main River
Context triple: [Römer, hasNearby, Main River]
  • A. River Main chosen
    The River Main is a major waterway in central Germany that flows through cities such as Frankfurt before joining the Rhine.
  • B. Emme River
    The Emme River is a Swiss river flowing through the Emmental region and the Swiss Plateau, known for its picturesque valleys and historical flooding events.
  • C. Or River
    The Or River is a waterway in Russia and Kazakhstan that flows through the southern Ural region before joining the Ural River.
  • D. Real River
    Real River is a watercourse in the Brazilian state of Sergipe, known for flowing through the northeastern region of the country and contributing to local ecosystems and communities.
  • E. Long River
    Long River is the English translation of the Chinese name for the Yangtze, Asia’s longest river and a major waterway in China.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351e70a748190af6f1b709a0e75e6 completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbc925d881909fac944bc7ce5407 completed March 14, 2026, 10:06 p.m.
Created at: March 12, 2026, 11:16 p.m.