Triple

T7461531
Position Surface form Disambiguated ID Type / Status
Subject OSLF E176259 entity
Predicate hasAcronym P43 FINISHED
Object OSLF E176259 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: OSLF | Statement: [OSLF, hasAcronym, OSLF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OSLF
Context triple: [OSLF, hasAcronym, OSLF]
  • A. OSLF chosen
    OSLF is the acronym for the U.S. Treasury Department’s Office of State and Local Finance, which focuses on fiscal issues affecting state and local governments.
  • B. OSL
    OSL is the three-letter IATA airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital.
  • C. OSDL
    OSDL (Open Source Development Labs) was a nonprofit organization that supported and promoted the development and adoption of the Linux operating system, particularly in enterprise environments.
  • D. SLSF
    SLSF was the reporting mark used by the St. Louis–San Francisco Railway, commonly known as the Frisco, a major Midwestern and Southern U.S. railroad.
  • E. OSSE
    OSSE is the District of Columbia’s state education agency responsible for overseeing public education policies, programs, and accountability across the city.
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3d6cf8c8190a31cac121d151d78 completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8345f629c8190889081e18bdfe6f7 completed March 28, 2026, 8:04 p.m.
Created at: March 27, 2026, 3:38 p.m.