Triple
T2329086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Plains station |
E48358
|
entity |
| Predicate | hasOverpass |
P38947
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [White Plains station, hasOverpass, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOverpass Context triple: [White Plains station, hasOverpass, yes]
-
A.
canProvideDirections
Indicates that one entity is able to give another entity guidance or instructions on how to reach a particular location or navigate a route.
-
B.
mapCoverage
Indicates the extent or area that is represented, covered, or included by a particular map.
-
C.
hasUnderpass
Indicates that one location or structure includes or is connected by an underpass beneath another feature or pathway.
-
D.
mapsFrom
Indicates that one entity is derived, transformed, or constructed based on data, structure, or content originating from another entity.
-
E.
coversCity
Indicates that one entity extends over, includes, or geographically encompasses the area of a specified city.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abcc30c5e881908c5d526d7e7491d0 |
completed | March 7, 2026, 6:56 a.m. |
| PD | Predicate disambiguation | batch_69abc5926d048190a535e3f23d41de2a |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcc2fa25c8190858c1c541b914f4c |
completed | March 7, 2026, 6:56 a.m. |
Created at: March 4, 2026, 7:50 p.m.