Triple

T14509357
Position Surface form Disambiguated ID Type / Status
Subject أوقية موريتانية E340354 entity
Predicate currencyCode P208 FINISHED
Object MRU E67886 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: MRU | Statement: [أوقية موريتانية, currencyCode, MRU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MRU
Context triple: [أوقية موريتانية, currencyCode, MRU]
  • A. MRU chosen
    MRU is the three-letter ISO 4217 currency code for the Mauritanian ouguiya, the official currency of Mauritania.
  • B. MRU
    MRU is the abbreviation for the Mano River Union, a regional organization that promotes economic cooperation and integration among West African countries along the Mano River.
  • C. MRIT
    MRIT is an abbreviation for the Matsushita Research Institute Tokyo, a Japanese research organization historically associated with Panasonic’s advanced technology and electronics R&D.
  • D. MRIA
    MRIA is the post-nominal title indicating membership of the Royal Irish Academy, an all-Ireland body of distinguished scholars and scientists.
  • E. MRIA
    MRIA is the abbreviation for Mattala Rajapaksa International Airport, a major international airport located in southern Sri Lanka.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e5b7b48190878be271840c265b completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6da26a308190bf86ed1edbe8d57e completed May 8, 2026, 4:59 a.m.
Created at: April 10, 2026, 1:21 a.m.