Triple

T19084801
Position Surface form Disambiguated ID Type / Status
Subject Pirmasens E467117 entity
Predicate hasPopulationRankInRhinelandPalatinate P25930 FINISHED
Object medium-sized city 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: medium-sized city | Statement: [Pirmasens, hasPopulationRankInRhinelandPalatinate, medium-sized city]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPopulationRankInRhinelandPalatinate
Context triple: [Pirmasens, hasPopulationRankInRhinelandPalatinate, medium-sized city]
  • A. rankWithinGermanStates
    Indicates the relative position or standing of an entity compared to others within the set of German federal states.
  • B. 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).
  • C. hasMunicipalAreaRankingInGermany
    Indicates that a municipality holds a specific rank or position in comparison to other municipalities in Germany based on its area size.
  • D. hasPopulationRankInRegion chosen
    Indicates that an entity has a specific population-based rank or position within a defined geographic region.
  • E. rankInGermanyByArea
    Indicates the position of an entity in an ordered list based on its area size within Germany.
  • 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_69d8dd04f4488190b1121cc53ef2bfd6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e346f57c8190a6299e09a0be9e05 completed April 20, 2026, 8:26 a.m.
PD Predicate disambiguation batch_69e4b9a604308190a3235184f9f2c056 completed April 19, 2026, 11:16 a.m.
Created at: April 10, 2026, 12:04 p.m.