Triple

T9321087
Position Surface form Disambiguated ID Type / Status
Subject Laurence Chaderton E224258 entity
Predicate workLocation P7 FINISHED
Object Cambridge, England E492 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: Cambridge, England | Statement: [Laurence Chaderton, workLocation, Cambridge, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cambridge, England
Context triple: [Laurence Chaderton, workLocation, Cambridge, England]
  • A. Cambridge, England chosen
    Cambridge, England is a historic university city on the River Cam renowned for the University of Cambridge and its longstanding contributions to education, science, and culture.
  • B. Cambridge
    Cambridge is a town in New Zealand known for its picturesque rural setting, equestrian culture, and proximity to the Waikato River.
  • C. Cambridge
    Cambridge is a historic and academically renowned city in Massachusetts, best known as the home of Harvard University and the Massachusetts Institute of Technology (MIT).
  • D. Cambridge
    Cambridge is a prominent city in the Greater Boston area best known as the home of Harvard University and the Massachusetts Institute of Technology (MIT).
  • E. Cambridge
    Cambridge is a city in southwestern Ontario, Canada, known as part of the Regional Municipality of Waterloo and situated along the Grand River.
  • 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_69ca8426d48481909596360f7791c7dd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd36f2bd288190bb1556a88d9e90f3 completed April 1, 2026, 3:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f3aad3cc819089c9d7ca96034bc5 completed April 4, 2026, 11:19 a.m.
Created at: March 30, 2026, 7:38 p.m.