Triple

T4013964
Position Surface form Disambiguated ID Type / Status
Subject Northern Province, Sri Lanka E90710 entity
Predicate significantCity P12871 FINISHED
Object Mannar E386427 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: Mannar | Statement: [Northern Province, Sri Lanka, significantCity, Mannar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mannar
Context triple: [Northern Province, Sri Lanka, significantCity, Mannar]
  • A. Mannar region chosen
    The Mannar region is a coastal area in northwestern Sri Lanka known for its shallow lagoons, rich marine biodiversity, and historical role as a trading hub.
  • B. Mapun
    Mapun is an Austronesian language spoken primarily by the Mapun people of the southern Philippines, particularly on Mapun (Cagayan de Sulu) Island in the Sulu Sea.
  • C. Maa
    Maa is a Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania.
  • D. Ballimaran
    Ballimaran is a historic, densely packed lane in Old Delhi known for its traditional shops, old havelis, and association with the poet Mirza Ghalib.
  • E. Eivissa
    Eivissa is the Catalan name for Ibiza, a popular Mediterranean island in Spain’s Balearic archipelago known for its beaches and nightlife.
  • 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_69aed95e44088190aff7d90a151b1b20 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa8ad6348190b71feaf8c18c90c2 completed March 9, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c73e6048190a59a8d8bc12c907d completed March 14, 2026, 11:54 a.m.
Created at: March 9, 2026, 3:35 p.m.