Triple

T4834897
Position Surface form Disambiguated ID Type / Status
Subject Perus E108033 entity
Predicate shortName P43 FINISHED
Object Perus E108033 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: Perus | Statement: [Perus, shortName, Perus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Perus
Context triple: [Perus, shortName, Perus]
  • A. Perus chosen
    Perus is the commonly used Finnish abbreviation for the Finns Party, a right-wing populist and nationalist political party in Finland.
  • B. Pervomaisk
    Pervomaisk is a city in southern Ukraine known as an industrial and transport hub situated along the Southern Bug River.
  • C. Base
    Base is Julia’s core standard library module that provides fundamental language functionality, built-in types, and essential operations.
  • D. Grund
    Grund is a historic, picturesque quarter of Luxembourg City known for its riverside setting, old architecture, and vibrant nightlife.
  • E. Basaseachi
    Basaseachi is a small town in Chihuahua, Mexico, known as the gateway to the nearby Basaseachic Falls and the surrounding Sierra Madre Occidental landscapes.
  • 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_69bd43fbe444819085cb970706ef73f7 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cde9b2081909f1aef81850d6007 completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4dda71e08190a28215f91405a4e1 completed March 21, 2026, 7:50 a.m.
Created at: March 20, 2026, 1:25 p.m.