Triple

T22343890
Position Surface form Disambiguated ID Type / Status
Subject Garding railway station E552341 entity
Predicate hasAddressLocality P7943 FINISHED
Object Garding NE NERFINISHED

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: Garding | Statement: [Garding railway station, hasAddressLocality, Garding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garding
Context triple: [Garding railway station, hasAddressLocality, Garding]
  • A. Garding chosen
    Garding is a small town in the Nordfriesland district of Schleswig-Holstein in northern Germany.
  • B. Garde
    Garde is the surname of American stage, film, and radio actress Betty Garde, known for her character roles in mid-20th-century entertainment.
  • C. Gardish
    Gardish is a 1993 Hindi action-drama film directed by Priyadarshan, known for Dimple Kapadia’s acclaimed performance alongside Jackie Shroff.
  • D. Garderen
    Garderen is a village in the Dutch province of Gelderland, known for its rural setting and location within the municipality of Barneveld.
  • E. Gardi
    Gardi is the nickname of Ibrahim Khan Gardi, an 18th-century Indian military commander renowned for leading artillery forces in the Third Battle of Panipat.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e494eec81909c4d2d51f69499d9 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15796b2288190b10e9402abf35fd3 completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:43 p.m.