Triple

T3337421
Position Surface form Disambiguated ID Type / Status
Subject Mozambican metical E70170 entity
Predicate legalStatus P64 FINISHED
Object legal tender LITERAL FINISHED

How this triple was built (1 step)

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: legal tender | Statement: [Mozambican metical, legalStatus, legal tender]

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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bc31b4819085f01e0b5a7cbc5d completed March 8, 2026, 5:28 p.m.
Created at: March 8, 2026, 3:12 p.m.