Triple

T1620049
Position Surface form Disambiguated ID Type / Status
Subject Harvard Bridge E35008 entity
Predicate crossesTo P29049 FINISHED
Object Cambridge E113375 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: [Harvard Bridge, crossesTo, Cambridge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cambridge
Context triple: [Harvard Bridge, crossesTo, Cambridge]
  • A. Cambridge, England
    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 chosen
    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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909b0738c8190b073e0ccec5e217d completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad607ead308190a599fac02c91e77e completed March 8, 2026, 11:41 a.m.
Created at: March 4, 2026, 7:28 p.m.