Triple
T26304841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J line |
E661651
|
entity |
| Predicate | runsThroughStation |
P161696
|
FINISHED |
| Object | Marcy Avenue |
—
|
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: Marcy Avenue | Statement: [J line, runsThroughStation, Marcy Avenue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runsThroughStation Context triple: [J line, runsThroughStation, Marcy Avenue]
-
A.
servesAsThroughStationFor
Indicates that a station functions as an intermediate (through) stop for a particular service, route, or journey rather than as its starting or ending point.
-
B.
passesThroughFacility
Indicates that something (such as a person, object, or shipment) moves through or is routed via a particular facility as part of its path or process.
-
C.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
D.
operatedBetweenStations
Indicates that an operation, such as a service or route, took place connecting or running between two specified stations.
-
E.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
- 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_69ee812dacfc81908484aade9120fba9 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6200ac60481909895c61d050b1338 |
completed | May 2, 2026, 4:02 p.m. |
| PD | Predicate disambiguation | batch_69f61b3a8ae0819090189fbd8eb19f2f |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61f109ef48190873bfe18638d2046 |
completed | May 2, 2026, 3:58 p.m. |
Created at: April 26, 2026, 10:18 p.m.