Triple

T14377285
Position Surface form Disambiguated ID Type / Status
Subject Gutar E356506 entity
Predicate legalDocument P358 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: [Gutar, legalDocument, Gutalagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gutalagen
Context triple: [Gutar, legalDocument, 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. Gutalac
    Gutalac is a rural municipality in the province of Zamboanga del Norte in the Philippines, known for its agricultural communities and inland, hilly terrain.
  • C. Ghunsa
    Ghunsa is a remote Himalayan village in eastern Nepal that serves as a key gateway and base for treks and expeditions around the Kangchenjunga region.
  • D. Gaddachauki
    Gaddachauki is a key Nepal–India land border crossing point located in Nepal’s Sudurpashchim Province.
  • E. Gangolli
    Gangolli is a coastal village in Karnataka, India, known for its fishing harbor and location near the confluence of multiple rivers with the Arabian Sea.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900949fc81909be0da1734c46645 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c5728fc819089ef3c7c34b10101 completed May 8, 2026, 2:37 a.m.
Created at: April 10, 2026, 1:16 a.m.