Triple
T16306132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simpson College |
E395915
|
entity |
| Predicate | cityProximity |
P36605
|
FINISHED |
| Object | near Des Moines, Iowa |
—
|
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: near Des Moines, Iowa | Statement: [Simpson College, cityProximity, near Des Moines, Iowa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityProximity Context triple: [Simpson College, cityProximity, near Des Moines, Iowa]
-
A.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
B.
featuresRegionalProximity
Indicates that one entity is located near or in close geographic proximity to a particular region or another entity.
-
C.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
D.
stateCapitalProximity
Indicates the spatial closeness or distance between a state’s capital city and another specified location.
-
E.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288d5619081909d0f8157cc487877 |
completed | April 17, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.