Triple
T24973886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transportation in Montgomery County, Maryland |
E624963
|
entity |
| Predicate | hasMetroStationArea |
P39430
|
FINISHED |
| Object | Bethesda |
—
|
NE NERFINISHED |
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: Bethesda | Statement: [Transportation in Montgomery County, Maryland, hasMetroStationArea, Bethesda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetroStationArea Context triple: [Transportation in Montgomery County, Maryland, hasMetroStationArea, Bethesda]
-
A.
hasMetroStations
chosen
Indicates that a place or area is served by one or more metro (subway) stations.
-
B.
hasMetroTerminus
Indicates that one location serves as the terminal (end) station of a metro line for another location.
-
C.
nearMetroStation
Indicates that one entity is located close to or within a short walking distance of a metro (subway) station.
-
D.
isWithinMetroArea
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
-
E.
hasMetroLine
Indicates that a location or area is served by, or connected to, a specific metro (subway) line.
- 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_69e2ff24512481908e9a72315b8d0354 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 6:01 a.m.