Triple

T14012162
Position Surface form Disambiguated ID Type / Status
Subject Ratnapura E337108 entity
Predicate roadConnectionTo P9041 FINISHED
Object Embilipitiya E471195 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: Embilipitiya | Statement: [Ratnapura, roadConnectionTo, Embilipitiya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Embilipitiya
Context triple: [Ratnapura, roadConnectionTo, Embilipitiya]
  • A. Embilipitiya chosen
    Embilipitiya is a rapidly developing town in southern Sri Lanka known as a commercial hub and gateway to the Udawalawe National Park.
  • B. Riyom
    Riyom is a town and local government area in Plateau State, central Nigeria, known for its distinctive rock formations and as a homeland of the Berom people.
  • C. Nzera
    Nzera is a settlement located within Tanzania’s Geita Region in East Africa.
  • D. Kasindi
    Kasindi is a border town in eastern Democratic Republic of the Congo, located near Uganda and serving as an important regional trade and transport hub.
  • E. Lusambo
    Lusambo is a town in the Democratic Republic of the Congo that once served as an important colonial and regional administrative center in the Kasai area.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc32b459c81908b652286f444e940 completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:19 p.m.