Triple

T22782615
Position Surface form Disambiguated ID Type / Status
Subject Wawa Airport E563877 entity
Predicate hasCityServed P3936 FINISHED
Object Wawa 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: Wawa | Statement: [Wawa Airport, hasCityServed, Wawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wawa
Context triple: [Wawa Airport, hasCityServed, Wawa]
  • A. Wawa chosen
    Wawa is a small town in northern Ontario, Canada, known for its iconic giant Canada goose statue and its history as a mining and forestry community.
  • B. Wawa
    Wawa was a king of the Medang Mataram Kingdom in Central Java, Indonesia, known from 10th-century inscriptions that place him among the later rulers of the early Javanese Hindu-Buddhist polity.
  • C. Wawa
    Wawa is a popular American chain of convenience stores and gas stations known for its fresh food, coffee, and made-to-order hoagies.
  • D. Wawa
    Wawa is a barangay (village-level administrative division) located in the municipality of Balagtas in the province of Bulacan, Philippines.
  • E. Waja
    Waja is a settlement located near the town of Alamata in northern Ethiopia.
  • 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_69e2455500788190b4b33030461f3bbd completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17c2ee4e88190951afb2abe69009f completed April 29, 2026, 3:34 a.m.
Created at: April 17, 2026, 3:28 p.m.