Triple

T16243123
Position Surface form Disambiguated ID Type / Status
Subject Negombo Beach E394302 entity
Predicate locatedIn P40 FINISHED
Object Negombo E78071 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: Negombo | Statement: [Negombo Beach, locatedIn, Negombo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Negombo
Context triple: [Negombo Beach, locatedIn, Negombo]
  • A. Negombo chosen
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • B. Kumba
    Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
  • C. Kumba
    Kumba is a major town in southwestern Cameroon known as a commercial hub and cultural crossroads where languages like Cameroonian Pidgin English are widely used.
  • D. Banjima
    Banjima is an Aboriginal Australian people traditionally associated with the Pilbara region of Western Australia, known for their distinct language and cultural heritage.
  • E. Chambeali
    Chambeali is an Indo-Aryan language spoken primarily in the Chamba region of Himachal Pradesh in northern India.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24560060c8190ace4f4c0bd0d886d completed April 17, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000edf64a88190a9dd0c591c742977 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:04 a.m.