Triple

T13110530
Position Surface form Disambiguated ID Type / Status
Subject Greiz E310957 entity
Predicate hasLandmark P105 FINISHED
Object Greiz Park E1079166 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: Greiz Park | Statement: [Greiz, hasLandmark, Greiz Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greiz Park
Context triple: [Greiz, hasLandmark, Greiz Park]
  • A. Greiz Park chosen
    Greiz Park is a historic landscaped public park in the town of Greiz, Germany, known for its scenic grounds and recreational green spaces.
  • B. Juergens Park
    Juergens Park is a public recreational park located in the city of Tomball, Texas.
  • C. Hagemeister Park
    Hagemeister Park was an early 20th-century athletic field in Green Bay, Wisconsin, best known as one of the original home grounds of the Green Bay Packers before they moved to City Stadium.
  • D. Ferris Park
    Ferris Park is a public recreational park located in the suburban city of Ballwin, Missouri.
  • E. Bohrer Park
    Bohrer Park is a public recreational park in Gaithersburg, Maryland, featuring amenities such as sports fields, walking paths, and family-friendly facilities.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817e4f408190b77c198b4157d77a completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdee8d1408190942ff455e7b1b6e2 completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 9:05 p.m.