Triple

T579356
Position Surface form Disambiguated ID Type / Status
Subject Old Gutnish E15023 entity
Predicate hasNotableText P7250 FINISHED
Object Gutalagen E72577 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: Gutalagen | Statement: [Old Gutnish, hasNotableText, Gutalagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gutalagen
Context triple: [Old Gutnish, hasNotableText, Gutalagen]
  • A. Gutalagen chosen
    Gutalagen is a medieval legal code from the island of Gotland, written in Old Gutnish and detailing the laws and customs of its inhabitants.
  • B. Rajpipla
    Rajpipla is a town in the Narmada district of Gujarat, India, historically known as the capital of the former princely state of Rajpipla.
  • C. Agrihan
    Agrihan is a remote volcanic island in the Northern Mariana Islands known for its large stratovolcano and rugged, sparsely populated landscape.
  • D. Jagaban
    Jagaban is the popular political nickname of Nigerian politician and current president Bola Ahmed Tinubu, often used to signify his influential “godfather” status in Nigerian politics.
  • E. Swayam
    Swayam is an Indian government-backed online learning platform that provides free Massive Open Online Courses (MOOCs) from schools, colleges, and universities across the country.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b6c358081908f458b9e3e208c0d completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a508a025308190ac35a5e3606de4de completed March 2, 2026, 3:48 a.m.
Created at: March 1, 2026, 7:33 p.m.