Triple
T36354192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Braidwood Nuclear Generating Station |
E895293
|
entity |
| Predicate | distanceFromChicago_km |
P204838
|
FINISHED |
| Object | about 80 |
—
|
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: about 80 | Statement: [Braidwood Nuclear Generating Station, distanceFromChicago_km, about 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromChicago_km Context triple: [Braidwood Nuclear Generating Station, distanceFromChicago_km, about 80]
-
A.
distanceFromChicagoTerminus
Indicates the measured distance of an entity from the Chicago terminus point along a specified route or network.
-
B.
distanceFromUrbana
Indicates the measured spatial distance between a given entity or location and Urbana.
-
C.
distanceToChicagoLoop
Indicates the spatial distance between a given location and Chicago’s central business district (the Loop).
-
D.
distanceFromChampaign
Indicates the measured distance between a given entity’s location and the location of Champaign.
-
E.
distanceFromChicagoUnionStation
Indicates the measured distance between a given location and Chicago Union Station.
- 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_69f76e4f437c8190a1af3ea2564f41f5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:09 p.m.