Triple

T17542981
Position Surface form Disambiguated ID Type / Status
Subject San Francisco OEM E427249 entity
Predicate shortName P43 FINISHED
Object SF OEM NE NERFINISHED

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: SF OEM | Statement: [San Francisco OEM, shortName, SF OEM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SF OEM
Context triple: [San Francisco OEM, shortName, SF OEM]
  • A. SF OEM chosen
    SF OEM is the abbreviated name for the San Francisco Office of Emergency Management, the city agency responsible for coordinating preparedness, response, and recovery efforts during emergencies and disasters.
  • B. OEM
    OEM refers to the Office for Emergency Management, a U.S. government agency created during World War II to coordinate civilian defense and federal emergency preparedness activities.
  • C. San Francisco OEM
    San Francisco OEM is the city’s Office of Emergency Management, responsible for coordinating preparedness, response, and recovery efforts for disasters and major incidents in San Francisco.
  • D. SF3
    SF3 is a nonprofit organization dedicated to promoting, supporting, and organizing activities related to fantasy and science fiction, including conventions and fan events.
  • E. OEMs
    OEMs (Original Equipment Manufacturers) are companies that design and produce vehicles or other end products into which components and technologies from suppliers like Mobileye are integrated.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889df6dc081908f67dbadc03c07ee completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4545f1fa08190870c9244d06cf5f6 completed April 19, 2026, 4:04 a.m.
Created at: April 10, 2026, 5:49 a.m.