Triple

T9583767
Position Surface form Disambiguated ID Type / Status
Subject Oberstdorf E231237 entity
Predicate hasMunicipalAreaRankingInGermany P89942 FINISHED
Object one of the largest by area — 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: one of the largest by area | Statement: [Oberstdorf, hasMunicipalAreaRankingInGermany, one of the largest by area]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMunicipalAreaRankingInGermany
Context triple: [Oberstdorf, hasMunicipalAreaRankingInGermany, one of the largest by area]
  • 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. hasLandkreis
    Indicates that an entity is associated with, or belongs to, a specific administrative district (Landkreis).
  • D. federalStateOfGermany
    Indicates that one entity is a federal state (Bundesland) that is a constituent state within the country of Germany.
  • 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. chosen

Provenance (4 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_69ca848161688190a68d514a0a9d5129 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99cebaf081908033536a53fbf668 completed April 1, 2026, 10:18 p.m.
PD Predicate disambiguation batch_69ccd59fd7408190b36831902e3f37f7 completed April 1, 2026, 8:21 a.m.
PDg Predicate description generation batch_69ccd93e90048190a2b0d7c5c195ba98 completed April 1, 2026, 8:37 a.m.
Created at: March 30, 2026, 8:06 p.m.