Triple
T24740961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muttontown, New York |
E618554
|
entity |
| Predicate | hasNearestRailService |
P25143
|
FINISHED |
| Object | Syosset station of the Long Island Rail Road |
—
|
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: Syosset station of the Long Island Rail Road | Statement: [Muttontown, New York, hasNearestRailService, Syosset station of the Long Island Rail Road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearestRailService Context triple: [Muttontown, New York, hasNearestRailService, Syosset station of the Long Island Rail Road]
-
A.
hasAdjacentRailService
Indicates that one location has rail service situated directly next to or immediately bordering it.
-
B.
hasRailServiceAt
Indicates that a rail transport service operates at or serves a particular location or facility.
-
C.
hasNearbyRailway
chosen
Indicates that one entity is located close to a railway associated with or relevant to another entity.
-
D.
nearestRailwayLine
Indicates that one railway line is the closest in distance to a given location or feature compared to all other railway lines.
-
E.
servesLocalTrains
Indicates that a station or facility provides service or stops specifically for local (non-express) train routes.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 18, 2026, 4:05 a.m.