Triple

T5447525
Position Surface form Disambiguated ID Type / Status
Subject Maschsee E122284 entity
Predicate locatedNear P294 FINISHED
Object Maschpark E379024 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: Maschpark | Statement: [Maschsee, locatedNear, Maschpark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maschpark
Context triple: [Maschsee, locatedNear, Maschpark]
  • A. Maschpark chosen
    Maschpark is a historic public park in central Hanover, Germany, known for its landscaped gardens and scenic lake beside the New Town Hall.
  • B. Germany Park
    Germany Park is a public recreational park located in University Park, Texas, offering green space and outdoor amenities for local residents.
  • C. Wuerfel Park
    Wuerfel Park is a baseball stadium in Traverse City, Michigan, that long served as the home field for the city’s minor league team before being renamed.
  • D. Falkeplatz
    Falkeplatz is a location in Chemnitz, Germany, known for hosting cultural institutions such as the Museum Gunzenhauser.
  • E. Westerpark
    Westerpark is a vibrant Amsterdam neighborhood and park area known for its cultural venues, green spaces, and former industrial buildings converted into creative hubs.
  • 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_69bd4640f52c81909e653ec361f66d76 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91d0df348190b3de010c87cb6d5d completed March 20, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4137ecf881908f3f036457b59281 completed March 22, 2026, 1:09 a.m.
Created at: March 20, 2026, 2:07 p.m.