Triple

T12599713
Position Surface form Disambiguated ID Type / Status
Subject Donald Lynden-Bell E300823 entity
Predicate placeOfDeath P21 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: [Donald Lynden-Bell, placeOfDeath, Cambridge, England]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cambridge, England
Context triple: [Donald Lynden-Bell, placeOfDeath, 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954d096d08190afa1f685bad68d35 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65e9e909081909b341398e7aae954 completed May 2, 2026, 8:29 p.m.
Created at: April 9, 2026, 5:09 p.m.