Triple

T5384080
Position Surface form Disambiguated ID Type / Status
Subject Shining Tor E113159 entity
Predicate nearbySettlement P350 FINISHED
Object Rainow E459528 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: Rainow | Statement: [Shining Tor, nearbySettlement, Rainow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rainow
Context triple: [Shining Tor, nearbySettlement, Rainow]
  • A. Rainow chosen
    Rainow is a rural village and civil parish in Cheshire, England, known for its scenic Peak District landscapes and historic farming community.
  • B. Lilienthal
    Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
  • C. Grevesmühlen
    Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
  • D. Marienfelde
    Marienfelde is a locality in the southern part of Berlin known for its residential areas and historical refugee reception center.
  • E. Birkenwerder
    Birkenwerder is a small municipality in the German state of Brandenburg, located just north of Berlin and known for its residential character and surrounding forests.
  • 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_69bd4436a1988190af18dcff7fd306b4 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd86f39edc81908e53973cef1bc0f3 completed March 20, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf295030b081909bea5e946aac098b completed March 21, 2026, 11:27 p.m.
Created at: March 20, 2026, 2:03 p.m.