Triple
T1744372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Forks, North Dakota |
E38303
|
entity |
| Predicate | hasFloodProtection |
P25048
|
FINISHED |
| Object | Greenway along Red River |
—
|
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: Greenway along Red River | Statement: [Grand Forks, North Dakota, hasFloodProtection, Greenway along Red River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodProtection Context triple: [Grand Forks, North Dakota, hasFloodProtection, Greenway along Red River]
-
A.
hasFloodProtectionProject
Indicates that a flood protection project exists or is implemented for the referenced entity.
-
B.
hasFloodControlStructure
Indicates that an entity possesses or is equipped with a structure designed to manage, control, or mitigate flooding.
-
C.
hasFloodProtectionInfrastructure
chosen
Indicates that there exists built or implemented infrastructure designed to protect against or mitigate flooding for the referenced entity.
-
D.
hasFloodHistory
Indicates that the subject has experienced one or more flood events in the past.
-
E.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.