Triple

T250610
Position Surface form Disambiguated ID Type / Status
Subject Thai baht E5137 entity
Predicate frequentlyTradedAgainst P8579 FINISHED
Object Japanese yen E2129 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: Japanese yen | Statement: [Thai baht, frequentlyTradedAgainst, Japanese yen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Japanese yen
Context triple: [Thai baht, frequentlyTradedAgainst, Japanese yen]
  • A. Japanese yen chosen
    The Japanese yen is Japan's official fiat currency and one of the world's most traded reserve currencies in global foreign exchange markets.
  • B. Chinese yuan
    The Chinese yuan is the official currency of the People's Republic of China and one of the world's major reserve and trading currencies.
  • C. South Korean won
    The South Korean won is the official currency of South Korea, known for its significant devaluation and subsequent reforms during the late-1990s Asian financial crisis.
  • D. Indonesian rupiah
    The Indonesian rupiah is the official currency of Indonesia, known for experiencing severe devaluation during the late-1990s Asian financial crisis.
  • E. Bank of Japan
    The Bank of Japan is the country's central bank, responsible for issuing currency, implementing monetary policy, and maintaining financial stability in Japan.
  • 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_69a257c4bf688190a46ebbf411ab7473 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a260c592cc8190bc642fcd248a1f1b completed Feb. 28, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69a37373426881909ce8766ad9c5778c completed Feb. 28, 2026, 11 p.m.
Created at: Feb. 28, 2026, 2:54 a.m.