Triple
T15097793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Stroudsburg |
E360584
|
entity |
| Predicate | distanceToAllentownPennsylvania |
P117307
|
FINISHED |
| Object | approximately 45 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 45 miles | Statement: [East Stroudsburg, distanceToAllentownPennsylvania, approximately 45 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAllentownPennsylvania Context triple: [East Stroudsburg, distanceToAllentownPennsylvania, approximately 45 miles]
-
A.
distanceToHarrisburg
Indicates the spatial distance between a given entity and the location of Harrisburg.
-
B.
distanceToScranton
Indicates the spatial distance between a given entity and the location Scranton.
-
C.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
-
D.
distanceToPittsburgh
Indicates the spatial distance between a given entity’s location and the city of Pittsburgh.
-
E.
distanceToPennsylvaniaBorder
Indicates the measured distance between a given location and the border of Pennsylvania.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0054f00388190a5123d9f4a869b96 |
completed | April 15, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69deb9645b9c8190a5712456dbd78029 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:04 a.m.