Triple

T5243209
Position Surface form Disambiguated ID Type / Status
Subject Soesterberg E118394 entity
Predicate locatedNear P294 FINISHED
Object Soest E323462 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: Soest | Statement: [Soesterberg, locatedNear, Soest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soest
Context triple: [Soesterberg, locatedNear, Soest]
  • A. Soest
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • B. Soest chosen
    Soest is a Dutch town and municipality in the central Netherlands known for its green surroundings and proximity to the Utrechtse Heuvelrug.
  • C. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • D. Wallhausen
    Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
  • E. Hagen
    Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b4da7308190856cdcee9cca41eb completed March 20, 2026, 4:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef82f2738819080c5a0963f6dbbb0 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:49 p.m.