Triple
T5610421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin, Maryland |
E147340
|
entity |
| Predicate | distanceToOceanCity |
P64650
|
FINISHED |
| Object | about 10 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: about 10 miles | Statement: [Berlin, Maryland, distanceToOceanCity, about 10 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToOceanCity Context triple: [Berlin, Maryland, distanceToOceanCity, about 10 miles]
-
A.
distanceToBaltimoreInMiles
Indicates the numerical distance, measured in miles, between a given location and the city of Baltimore.
-
B.
distanceToLewes
Indicates the measured spatial distance between a given entity and the location Lewes.
-
C.
distanceFromBoston
Indicates the spatial distance between a given entity’s location and the city of Boston.
-
D.
distanceToNorfolkVirginia
Indicates the spatial distance between a given entity or location and Norfolk, Virginia.
-
E.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0211dfc88819097b6d4254a61f65a |
completed | March 22, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:39 p.m.