Triple
T22794014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Highway 101 (Ontario) |
E564191
|
entity |
| Predicate | passesThrough |
P225
|
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: [Highway 101 (Ontario), passesThrough, Wawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wawa Context triple: [Highway 101 (Ontario), passesThrough, 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 Chadic language spoken by the Waja people in northeastern Nigeria.
- 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cd81794819091b528600e322d7b |
completed | April 29, 2026, 3:36 a.m. |
Created at: April 17, 2026, 3:30 p.m.