Triple

T10934084
Position Surface form Disambiguated ID Type / Status
Subject Les Ulis E258282 entity
Predicate hasTwinTown P919 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: [Les Ulis, hasTwinTown, Harlow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harlow
Context triple: [Les Ulis, hasTwinTown, 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770ae073881909720febe9f5f296a completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2176328448190bbce6735ec97507a completed April 17, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:23 p.m.