Triple

T22381562
Position Surface form Disambiguated ID Type / Status
Subject Delhi, Iowa E553286 entity
Predicate hasNearbyWaterBody P1489 FINISHED
Object Lake Delhi 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: Lake Delhi | Statement: [Delhi, Iowa, hasNearbyWaterBody, Lake Delhi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Delhi
Context triple: [Delhi, Iowa, hasNearbyWaterBody, Lake Delhi]
  • A. Lake Delhi chosen
    Lake Delhi is a popular recreational reservoir in northeastern Iowa known for boating, fishing, and lakeside homes.
  • B. Lake Audy
    Lake Audy is a scenic lake in Manitoba, Canada, known for its wildlife viewing, camping, and recreational opportunities within Riding Mountain National Park.
  • C. Lake Ross
    Lake Ross is a man-made reservoir formed by damming the Ross River, primarily used for water storage and regional water supply.
  • D. Lake Newport
    Lake Newport is a man-made residential and recreational lake located in the planned community of Reston, Virginia.
  • E. Lake Newport
    Lake Newport is a recreational reservoir within Mill Creek Park in Youngstown, Ohio, known for activities such as boating, fishing, and scenic nature viewing.
  • 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_69e11e4c03248190a26a5060ea6973ee completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1582c05fc8190836ae008426177a5 completed April 29, 2026, 1 a.m.
Created at: April 16, 2026, 8:45 p.m.