Triple
T908803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burlington, Iowa, United States |
E19609
|
entity |
| Predicate | hasRiverfrontFeature |
P1495
|
FINISHED |
| Object | levee walkway |
—
|
LITERAL 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: levee walkway | Statement: [Burlington, Iowa, United States, hasRiverfrontFeature, levee walkway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiverfrontFeature Context triple: [Burlington, Iowa, United States, hasRiverfrontFeature, levee walkway]
-
A.
hasWaterfrontArea
Indicates that an entity possesses or includes an area directly adjacent to or bordering a body of water.
-
B.
hasRiver
Indicates that a location or area contains, is traversed by, or is directly associated with a river.
-
C.
hasCityOnRiver
Indicates that a city is located on or along the course of a particular river.
-
D.
hasMajorCityOnRiver
Indicates that a major city is located on and directly associated with a particular river.
-
E.
hasUrbanFeature
chosen
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
- F. None of above.
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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bcad2481908b83575b2fb80d14 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b28ff5948190982c4439eadf9d87 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.