Triple
T11223526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Vernon East station |
E265634
|
entity |
| Predicate | distanceToGrandCentral |
P38946
|
FINISHED |
| Object | approximately 14 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 14 miles | Statement: [Mount Vernon East station, distanceToGrandCentral, approximately 14 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGrandCentral Context triple: [Mount Vernon East station, distanceToGrandCentral, approximately 14 miles]
-
A.
distanceFromGrandCentral
chosen
Indicates the spatial distance between a given entity and Grand Central.
-
B.
distanceFromPennStation
Indicates the physical distance between a given location and Penn Station.
-
C.
distanceFromStPancras
Indicates the spatial distance between an entity and St Pancras.
-
D.
distanceFromDowntown
Indicates the physical distance between a given location and the central downtown area.
-
E.
distance to Midtown Manhattan (miles)
Indicates the physical separation between a location and Midtown Manhattan, measured in miles.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ec8fb08190b27144ab65f85957 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d75cfbbb188190861efd5d94fe27da |
completed | April 9, 2026, 8:02 a.m. |
Created at: April 8, 2026, 9:30 p.m.