Triple
T21961781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac-Mac Falls |
E542347
|
entity |
| Predicate | hasNearbyAttraction |
P2064
|
FINISHED |
| Object | Lisbon Falls |
—
|
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: Lisbon Falls | Statement: [Mac-Mac Falls, hasNearbyAttraction, Lisbon Falls]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisbon Falls Context triple: [Mac-Mac Falls, hasNearbyAttraction, Lisbon Falls]
-
A.
Lisbon Falls
chosen
Lisbon Falls is a scenic waterfall in South Africa’s Mpumalanga province, renowned for its dramatic drop and lush surroundings along the popular Panorama Route.
-
B.
Lisbon Falls
Lisbon Falls is a small town in Maine, United States, known for its historic mill heritage and scenic location along the Androscoggin River.
-
C.
Slate Falls
Slate Falls is a small rural community located within the township of Addington Highlands in eastern Ontario, Canada.
-
D.
Florence Falls
Florence Falls is a picturesque twin waterfall and popular swimming spot set amid monsoon forest in Australia’s Litchfield National Park.
-
E.
Sturtevant Falls
Sturtevant Falls is a popular waterfall in the San Gabriel Mountains of Southern California, known for its scenic hiking trail and lush canyon setting.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124572738819098cc669aafa53cc6 |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8 p.m.