Triple

T16463295
Position Surface form Disambiguated ID Type / Status
Subject Green Belt of Frankfurt am Main E399864 entity
Predicate traversedBy P225 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: [Green Belt of Frankfurt am Main, traversedBy, Main River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Main River
Context triple: [Green Belt of Frankfurt am Main, traversedBy, Main River]
  • A. You River
    The You River is a tributary waterway in southern China that feeds into the larger Yuan River system.
  • B. River Main chosen
    The River Main is a major waterway in central Germany that flows through cities such as Frankfurt before joining the Rhine.
  • C. River Main
    River Main is a river in Northern Ireland that flows through County Antrim and joins the River Braid before eventually reaching the sea via Lough Neagh and the Lower Bann.
  • D. Kako River
    The Kako River is a river in Japan whose name was used for the Imperial Japanese Navy cruiser Kako.
  • E. Sure river
    The Sure river is a Swiss watercourse that drains Lake Sempach and flows through the canton of Lucerne before joining larger river systems.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d824cd881909b1f2fd40e14ee35 completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f555f6081908b1f0d524b6fb9a7 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.