Triple

T38185631
Position Surface form Disambiguated ID Type / Status
Subject Gödringen E1005307 entity
Predicate hasGermanState P56632 FINISHED
Object Niedersachsen E4364 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: Niedersachsen | Statement: [Gödringen, hasGermanState, Niedersachsen]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGermanState
Context triple: [Gödringen, hasGermanState, Niedersachsen]
  • A. federalStateOfGermany chosen
    Indicates that one entity is a federal state (Bundesland) that is a constituent state within the country of Germany.
  • B. oneOfGermanys
    Indicates that something or someone belongs to the set of entities that are part of, originate from, or are associated with Germany.
  • C. containsGermanSpeakingArea
    Indicates that one entity geographically includes an area where German is predominantly spoken.
  • D. hasGermanMunicipalityKey
    Indicates that an entity is associated with a specific official German municipality key (Amtlicher Gemeindeschlüssel) identifying its municipality.
  • E. rankWithinGermanStates
    Indicates the relative position or standing of an entity compared to others within the set of German federal states.
  • F. None of above.

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_69f76dbc22c481908139b694ffde7a0c completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fe7bfc94bc81909eeec946e8c1c450 completed May 9, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41c26ddac081909c784842b64ed6a6 completed June 29, 2026, 12:55 a.m.
PD Predicate disambiguation batch_69fe7b74a1188190886f128e07f712da completed May 9, 2026, 12:10 a.m.
Created at: May 3, 2026, 4:29 p.m.