Triple

T19150339
Position Surface form Disambiguated ID Type / Status
Subject Southern Province E468787 entity
Predicate hasHistoricCity P3786 FINISHED
Object Matara 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: Matara | Statement: [Southern Province, hasHistoricCity, Matara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matara
Context triple: [Southern Province, hasHistoricCity, Matara]
  • A. Matara
    Matara is a major coastal city in southern Sri Lanka known for its historic fort, beaches, and role as a regional commercial and transport hub.
  • B. Matara District
    Matara District is an administrative district in southern Sri Lanka known for its coastal cities, historical sites, and agricultural hinterland.
  • C. Matara, Sri Lanka chosen
    Matara, Sri Lanka is a major coastal city in the Southern Province known for its historic fort, beaches, and role as a regional commercial and cultural hub.
  • D. Unawatuna
    Unawatuna is a popular coastal town in southern Sri Lanka known for its palm-fringed beach, coral-rich bay, and laid-back tourist atmosphere.
  • E. Vilankulo
    Vilankulo is a coastal town in southern Mozambique known as the main gateway to the nearby Bazaruto Archipelago and its popular beach and marine tourism.
  • 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e97c42348190875a2f5b5bc0b99e completed April 20, 2026, 8:53 a.m.
Created at: April 10, 2026, 12:06 p.m.