Triple

T19296493
Position Surface form Disambiguated ID Type / Status
Subject Osaka Securities Exchange E482577 entity
Predicate abbreviation P43 FINISHED
Object OSE 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: OSE | Statement: [Osaka Securities Exchange, abbreviation, OSE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OSE
Context triple: [Osaka Securities Exchange, abbreviation, OSE]
  • A. OSE chosen
    OSE is the abbreviation for the Osaka Securities Exchange, a major Japanese stock exchange based in Osaka.
  • B. OSE
    OSE is the Oslo Stock Exchange, Norway’s primary securities market for trading shares, bonds, and other financial instruments.
  • C. OSE
    OSE is the Seattle city government’s Office of Sustainability and Environment, which leads policies and programs to advance environmental stewardship and climate action.
  • D. OSE
    OSE is the Greek national railway organization responsible for owning and managing the country’s railway infrastructure.
  • E. OSE
    OSE is the Office of Surveillance and Epidemiology within the U.S. Food and Drug Administration that monitors the safety and effectiveness of drugs and therapeutic biologics after they reach the market.
  • 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_69d8e8cf61b0819096fe3e4107827c4e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fc85e8988190a98bc291121f0153 completed April 20, 2026, 10:14 a.m.
Created at: April 10, 2026, 1:31 p.m.