Triple
T16518924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iowa flood of 2008 |
E401262
|
entity |
| Predicate | affectedArea |
P1586
|
FINISHED |
| Object | Waterloo, Iowa |
E59849
|
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: Waterloo, Iowa | Statement: [Iowa flood of 2008, affectedArea, Waterloo, Iowa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waterloo, Iowa Context triple: [Iowa flood of 2008, affectedArea, Waterloo, Iowa]
-
A.
Waterloo, Iowa
chosen
Waterloo, Iowa is a mid-sized city in northeastern Iowa known as an industrial and commercial hub of the Cedar Valley region along the Cedar River.
-
B.
Wheatland, Iowa
Wheatland, Iowa is a small rural city in eastern Iowa known for its agricultural community and location within Clinton County.
-
C.
Waverly, Iowa
Waverly, Iowa is a small city in northeastern Iowa known as the county seat of Bremer County and home to Wartburg College.
-
D.
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.
-
E.
Bloomfield, Iowa
Bloomfield, Iowa is a small city in Davis County known for its historic town square and role as a local agricultural and commercial center in southeastern 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7ec45c8190b5e2c4a5f707e332 |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006086c0a881908976103f8a144f69 |
completed | May 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 5:14 a.m.