Triple

T19698850
Position Surface form Disambiguated ID Type / Status
Subject Anga E473037 entity
Predicate borderedBy P224 FINISHED
Object Vanga NE NERFINISHED

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: Vanga | Statement: [Anga, borderedBy, Vanga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vanga
Context triple: [Anga, borderedBy, Vanga]
  • A. Vanga chosen
    Vanga was an ancient historical region in eastern Bengal, centered in what is now southern Bangladesh and parts of the Indian state of West Bengal.
  • B. Vengola
    Vengola is a village in the Ernakulam district of Kerala, India, known for its rural character within the Kochi metropolitan region.
  • C. Viliya
    Viliya is an alternative name for the Neris River, a major river flowing through Belarus and Lithuania and a key tributary of the Neman.
  • D. Vrakuňa
    Vrakuňa is a borough of Bratislava, Slovakia, located in the eastern part of the city.
  • E. Vereya
    Vereya is a small historic town in Russia that was once part of the former Moscow Governorate.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e642b426608190a46abec3652a6ca0 completed April 20, 2026, 3:13 p.m.
Created at: April 10, 2026, 1:46 p.m.