Triple

T12982754
Position Surface form Disambiguated ID Type / Status
Subject Matara railway station E321692 entity
Predicate locatedIn P40 FINISHED
Object Matara E323360 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: Matara | Statement: [Matara railway station, locatedIn, Matara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matara
Context triple: [Matara railway station, locatedIn, Matara]
  • A. Matara chosen
    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. 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.
  • D. 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.
  • E. Ampara
    Ampara is a major town in Sri Lanka known as an agricultural and administrative center in the island’s Eastern Province.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e5ca33481909a6cb06c636889f9 completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7460999c081908c8d84caf6c04985 completed May 3, 2026, 12:56 p.m.
Created at: April 9, 2026, 8:39 p.m.