Triple

T1412644
Position Surface form Disambiguated ID Type / Status
Subject Common Monetary Area E31838 entity
Predicate currencyPeg P26645 FINISHED
Object Swazi lilangeni E103007 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: Swazi lilangeni | Statement: [Common Monetary Area, currencyPeg, Swazi lilangeni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swazi lilangeni
Context triple: [Common Monetary Area, currencyPeg, Swazi lilangeni]
  • A. Mabalako
    Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
  • B. Lilangeni chosen
    The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
  • C. Lomwe
    Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
  • D. Mtiuleti
    Mtiuleti is a mountainous historical region in northeastern Georgia known for its rugged landscapes and traditional highland villages.
  • E. Maphelane
    Maphelane is a coastal nature reserve in South Africa known for its high vegetated dunes, rich birdlife, and diverse estuarine and marine habitats within the iSimangaliso Wetland Park.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c48ff58c8190aeaf09d3e7cad7c7 completed March 1, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace57ec2d88190b06d0f20e3b52462 completed March 8, 2026, 2:57 a.m.
Created at: March 1, 2026, 7:59 p.m.