Triple

T3090698
Position Surface form Disambiguated ID Type / Status
Subject Peter Orlovsky E64473 entity
Predicate residence P75 FINISHED
Object San Francisco E242 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: San Francisco | Statement: [Peter Orlovsky, residence, San Francisco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Francisco
Context triple: [Peter Orlovsky, residence, San Francisco]
  • A. San Francisco chosen
    San Francisco is a major coastal city in Northern California known for its hilly landscape, iconic Golden Gate Bridge, and role as a historic center of technology and counterculture.
  • B. Sausalito
    Sausalito is a picturesque waterfront city in Northern California known for its hillside homes, art galleries, and views of the San Francisco Bay.
  • C. San Jose
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • D. Sacramento
    Sacramento is the capital city of the U.S. state of California, known for its role as the state’s political center and its historic roots in the Gold Rush era.
  • E. Oakland
    Oakland is a major port city in the San Francisco Bay Area known for its cultural diversity, progressive politics, and significant role in West Coast shipping and industry.
  • 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_69ad857c97d88190b26f9b1c90839c77 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada20d8f788190b05b8b6b5042bc1a completed March 8, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2035c404881908635c8514c8c1399 completed March 12, 2026, 12:05 a.m.
Created at: March 8, 2026, 3:03 p.m.