Triple
T33178484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kedzie Bridge |
E849251
|
entity |
| Predicate | crossesNamedFeature |
P185240
|
FINISHED |
| Object | Red Cedar River |
—
|
NE NERFINISHED |
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: Red Cedar River | Statement: [Kedzie Bridge, crossesNamedFeature, Red Cedar River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesNamedFeature Context triple: [Kedzie Bridge, crossesNamedFeature, Red Cedar River]
-
A.
namedFeature
Indicates that an entity has a specific feature or attribute that is explicitly given a name.
-
B.
crossesBoroughFeature
Indicates that one entity extends across or passes through a geographic feature that spans multiple boroughs.
-
C.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
D.
crossesNear
Indicates that one entity passes across the path or area of another entity at a location that is close to, but not directly intersecting, the other entity.
-
E.
featuresCrossoverWith
Indicates that one entity includes or participates in a crossover event or collaboration with another entity.
- F. None of above. chosen
Provenance (4 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_69f3495d06508190b0b7729982982cea |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: May 1, 2026, 1:29 a.m.