Triple
T20030122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gold Line (MARTA) |
E495098
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | East Point station |
—
|
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: East Point station | Statement: [Gold Line (MARTA), hasStation, East Point station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: East Point station Context triple: [Gold Line (MARTA), hasStation, East Point station]
-
A.
East Point station
chosen
East Point station is a rapid transit stop on Atlanta’s MARTA rail system serving the city of East Point, Georgia.
-
B.
Bayside Station
Bayside Station is a monorail stop on Tokyo Disney Resort’s Disney Resort Line serving nearby hotels and resort facilities.
-
C.
Bayside station
Bayside station is a Long Island Rail Road commuter rail stop in the Bayside neighborhood of Queens, New York City.
-
D.
Old Town station
Old Town station is a commuter rail stop in Lewisville, Texas, serving Denton County’s A-train line.
-
E.
DeBary station
DeBary station is a SunRail commuter rail station in DeBary, Florida, serving as the northern endpoint of the system’s line.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66291a00c8190b0b895909f32d623 |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.