Triple

T12631020
Position Surface form Disambiguated ID Type / Status
Subject Lake Müritz E301640 entity
Predicate rankingByAreaInGermany P89198 FINISHED
Object second-largest lake in Germany LITERAL 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: second-largest lake in Germany | Statement: [Lake Müritz, rankingByAreaInGermany, second-largest lake in Germany]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rankingByAreaInGermany
Context triple: [Lake Müritz, rankingByAreaInGermany, second-largest lake in Germany]
  • A. rankInGermanyByArea chosen
    Indicates the position of an entity in an ordered list based on its area size within Germany.
  • B. hasMunicipalAreaRankingInGermany
    Indicates that a municipality holds a specific rank or position in comparison to other municipalities in Germany based on its area size.
  • C. rankWithinGermanStates
    Indicates the relative position or standing of an entity compared to others within the set of German federal states.
  • D. rankAmongGermanStates
    Indicates the relative position or standing of a German state when ordered or compared to other German states by a specific criterion (such as size, population, or performance).
  • E. rankInGermanEmpireByArea
    Indicates the ordinal position of an entity when all entities in the German Empire are ordered by their land area.
  • F. None of above.

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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961ae493481908f82e0d05dce20bd completed April 10, 2026, 8:46 p.m.
PD Predicate disambiguation batch_69d960b47130819097e1162ed4fc993a completed April 10, 2026, 8:42 p.m.
Created at: April 9, 2026, 5:15 p.m.