Triple
T16984338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aberdeen, Maryland |
E412023
|
entity |
| Predicate | distanceToBaltimore |
P33616
|
FINISHED |
| Object | approximately 30 miles |
—
|
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 30 miles | Statement: [Aberdeen, Maryland, distanceToBaltimore, approximately 30 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBaltimore Context triple: [Aberdeen, Maryland, distanceToBaltimore, approximately 30 miles]
-
A.
distanceToBaltimoreInMiles
chosen
Indicates the numerical distance, measured in miles, between a given location and the city of Baltimore.
-
B.
distanceFromBaltimorePennStation
Indicates the measured distance between a given location and Baltimore Penn Station.
-
C.
distanceToAnnapolisMiles
Indicates the physical distance, measured in miles, between a given location and Annapolis.
-
D.
distanceToWashingtonDC
Indicates the physical distance between a given location and Washington, D.C.
-
E.
distanceToOceanCity
Indicates the measured distance between a given location and Ocean City.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d18a0bf881908c449f499eb86495 |
completed | April 18, 2026, 6:46 p.m. |
| PD | Predicate disambiguation | batch_69e35d4dff4881909b384e30f2d36bff |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.