Triple

T14090227
Position Surface form Disambiguated ID Type / Status
Subject River Stort E339107 entity
Predicate flowsThrough P225 FINISHED
Object Harlow E163496 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: Harlow | Statement: [River Stort, flowsThrough, Harlow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harlow
Context triple: [River Stort, flowsThrough, Harlow]
  • A. Harlow
    Harlow is a 1965 biographical drama film about the life and career of Hollywood actress Jean Harlow.
  • B. Harlow chosen
    Harlow is a town in Essex, England, known as a post-war New Town with significant residential, commercial, and industrial development.
  • C. Peabody
    Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
  • D. Haddon Heights
    Haddon Heights is a small suburban borough in southern New Jersey known for its historic homes, tree-lined streets, and close-knit community.
  • E. Marford
    Marford is a village in Wrexham County Borough, Wales, known for its distinctive Gothic-style architecture and historic character.
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5ee3213c8190af2853a2a5b302a2 completed April 14, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0a7aab88190949cf1fd8e11b050 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:21 p.m.