Triple

T4992931
Position Surface form Disambiguated ID Type / Status
Subject Downtown San Francisco E112174 entity
Predicate hasStreet P959 FINISHED
Object Kearny Street E136697 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: Kearny Street | Statement: [Downtown San Francisco, hasStreet, Kearny Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kearny Street
Context triple: [Downtown San Francisco, hasStreet, Kearny Street]
  • A. Kearny Street chosen
    Kearny Street is a major historic thoroughfare in San Francisco that runs through downtown and Chinatown, lined with shops, offices, and cultural landmarks.
  • B. Monroe Street
    Monroe Street is a major east–west thoroughfare in downtown Chicago, Illinois, running through the city’s central business and cultural districts.
  • C. Hudson Street
    Hudson Street is a major north–south thoroughfare in Lower Manhattan, New York City, running through neighborhoods such as Tribeca and the West Village.
  • D. Keefer Street
    Keefer Street is a notable thoroughfare in Vancouver’s Chinatown, known for its historic buildings, cultural landmarks, and vibrant local businesses.
  • E. Bayard Street
    Bayard Street is a prominent thoroughfare in Manhattan’s Chinatown known for its dense concentration of Chinese restaurants, shops, and cultural landmarks.
  • 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_69bd441be7bc8190b530362d427b97d2 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd729d3d448190a414a003a75104f6 completed March 20, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1351018b48190910c3dad6c0f9850 completed March 23, 2026, 12:41 p.m.
Created at: March 20, 2026, 1:34 p.m.