Triple

T4217225
Position Surface form Disambiguated ID Type / Status
Subject Krumme Lanke E94247 entity
Predicate nearby P350 FINISHED
Object Grunewald forest E25888 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: Grunewald forest | Statement: [Krumme Lanke, nearby, Grunewald forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grunewald forest
Context triple: [Krumme Lanke, nearby, Grunewald forest]
  • A. Grunewald forest chosen
    Grunewald forest is a large woodland and recreational area in western Berlin, known for its lakes, walking trails, and natural landscapes.
  • B. Schorfheide forest
    Schorfheide forest is a large historic woodland and former royal hunting reserve in Brandenburg, Germany, known for its rich biodiversity and use as a retreat by political leaders.
  • C. Ussishkin Forest
    Ussishkin Forest is a commemorative woodland in Israel named in honor of Zionist leader Menachem Ussishkin, serving as both a natural recreation area and a memorial site.
  • D. Reichswald Forest
    Reichswald Forest is a large wooded area in western Germany near the Dutch border, historically notable as the site of intense fighting during World War II.
  • E. Tuchola Forest
    Tuchola Forest is one of Poland’s largest and most pristine forest complexes, known for its extensive pine woods, lakes, and protected natural landscapes.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34beb470481909ceff19195417f19 completed March 12, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b76f07b4819097b59868af43b611 completed March 14, 2026, 7:30 p.m.
Created at: March 12, 2026, 11:04 p.m.