Triple

T3446802
Position Surface form Disambiguated ID Type / Status
Subject Carmen Cortez E72698 entity
Predicate affiliation P10 FINISHED
Object OSS E16815 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: OSS | Statement: [Carmen Cortez, affiliation, OSS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OSS
Context triple: [Carmen Cortez, affiliation, OSS]
  • A. OSS chosen
    OSS was the World War II-era U.S. intelligence agency that served as the predecessor to the Central Intelligence Agency (CIA).
  • B. OSSE
    OSSE is the District of Columbia’s state education agency responsible for overseeing public education policies, programs, and accountability across the city.
  • C. OSS Society
    The OSS Society is a nonprofit organization dedicated to honoring the legacy and preserving the history of the World War II-era Office of Strategic Services and its role in U.S. intelligence and special operations.
  • D. Oss
    Oss is a municipality and industrial city in the southern Netherlands, known historically for its pharmaceutical and meat-processing industries.
  • E. OSSPI
    OSSPI is a U.S. federal office that leads government-wide efforts to improve performance, customer experience, and shared services across agencies.
  • 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_69ad85b05c848190b7a28ceec2bd7b74 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba6efb188190b989fa4d6f28e16b completed March 8, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360e32ba08190bcd2f3cbe963c443 completed March 13, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:16 p.m.