Triple
T25077814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willow Springs station |
E628099
|
entity |
| Predicate | distanceFromUnionStation_miles |
P75017
|
FINISHED |
| Object | approximately 16 |
—
|
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: approximately 16 | Statement: [Willow Springs station, distanceFromUnionStation_miles, approximately 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromUnionStation_miles Context triple: [Willow Springs station, distanceFromUnionStation_miles, approximately 16]
-
A.
distanceFromGrandCentral
Indicates the spatial distance between a given entity and Grand Central.
-
B.
distanceFromChicagoUnionStation
chosen
Indicates the measured distance between a given location and Chicago Union Station.
-
C.
distanceFromSouthStation
Indicates the measured distance between a given location or entity and South Station.
-
D.
distanceFromPennStation
Indicates the physical distance between a given location and Penn Station.
-
E.
distanceFromStPancras
Indicates the spatial distance between an entity and St Pancras.
- 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_69e2ff2e73f881909992bf3eda5c25cb |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 18, 2026, 6:21 a.m.