Triple

T1193021
Position Surface form Disambiguated ID Type / Status
Subject Otto Frisch E25604 entity
Predicate placeOfDeath P21 FINISHED
Object Cambridge 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 | Statement: [Otto Frisch, placeOfDeath, Cambridge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cambridge
Context triple: [Otto Frisch, placeOfDeath, Cambridge]
  • 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. Oxford
    Oxford is a historic English city renowned for its prestigious university, distinctive architecture, and long-standing academic and cultural influence.
  • C. Oxford
    Oxford is a small city in northeastern Alabama known for its location in the Anniston–Oxford metropolitan area and proximity to the Talladega National Forest.
  • D. City of Cambridge
    The City of Cambridge is a historic and culturally vibrant Massachusetts city known for its prestigious universities, diverse neighborhoods, and rich architectural heritage.
  • E. Cambridge city center
    Cambridge city center is the main commercial and cultural hub of Cambridge, Massachusetts, encompassing historic districts, universities, shops, and restaurants.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd761ef08190b431b80f326d1ab2 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce59fe3c8190a07d84c570b7b2fe completed March 8, 2026, 1:18 a.m.
Created at: March 1, 2026, 7:45 p.m.