Triple

T3005760
Position Surface form Disambiguated ID Type / Status
Subject Hermsdorf E81896 entity
Predicate locatedNear P294 FINISHED
Object Tegeler Forst E15561 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: Tegeler Forst | Statement: [Hermsdorf, locatedNear, Tegeler Forst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tegeler Forst
Context triple: [Hermsdorf, locatedNear, Tegeler Forst]
  • A. Tegeler Forst chosen
    Tegeler Forst is a large forested area in the Berlin district of Tegel, known for its natural landscapes, walking trails, and recreational opportunities.
  • B. Tempelhofer Feld
    Tempelhofer Feld is a vast public park and former airport in Berlin, Germany, known for its open runways, recreational spaces, and historical significance, including its role in the Berlin Airlift.
  • C. Babelsberg Park
    Babelsberg Park is a historic landscaped park in Potsdam, Germany, known for its picturesque lakeside setting, neo-Gothic Babelsberg Palace, and 19th-century English-style garden design.
  • D. 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.
  • E. Tiergarten
    Tiergarten is a large central park in Berlin known for its expansive green spaces, monuments, and cultural landmarks.
  • 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_69ad8b1c4de88190a83b7cefaa1f2842 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a15ad9c81908255003bdb38d603 completed March 8, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e56bbd881909680248acca30557 completed March 11, 2026, 8:56 a.m.
Created at: March 8, 2026, 3 p.m.