Triple
T15721707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bremer County, Iowa |
E381109
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Denver, Iowa |
E287278
|
NE 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: Denver, Iowa | Statement: [Bremer County, Iowa, hasCity, Denver, Iowa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denver, Iowa Context triple: [Bremer County, Iowa, hasCity, Denver, Iowa]
-
A.
Denver, Iowa
chosen
Denver, Iowa is a small city in Bremer County known for its close-knit community, quality schools, and location within northeastern Iowa’s Cedar Valley region.
-
B.
Washington, Iowa
Washington, Iowa is a small city in southeastern Iowa known for its historic downtown, agricultural surroundings, and role as a local commercial and cultural hub.
-
C.
Danville, Iowa
Danville, Iowa is a small rural city in southeastern Iowa known for its close-knit community and agricultural surroundings.
-
D.
Fort Dodge, Iowa
Fort Dodge, Iowa is a small industrial city in north-central Iowa known historically for its gypsum mining, manufacturing, and role as a regional commercial hub.
-
E.
Greeley, Iowa
Greeley, Iowa is a small rural town in Delaware County in northeastern Iowa.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb0b51081908e652ec4992296fa |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff87657528819098880c84f7cb1610 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:45 a.m.