Triple
T3855506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syosset station |
E90002
|
entity |
| Predicate | commuterRail |
P21806
|
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: [Syosset station, commuterRail, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commuterRail Context triple: [Syosset station, commuterRail, yes]
-
A.
commuterRailMode
chosen
Indicates that the relationship involves travel or transportation specifically by commuter rail as the mode of transit between the related entities.
-
B.
rapidTransitSystem
Indicates a transportation relationship where people or goods are moved via a high-capacity, high-frequency public transit system designed for rapid travel over urban or regional routes.
-
C.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
-
D.
isBusiestPassengerRailLineIn
Indicates that a passenger rail line is the one with the highest level of use or traffic within a specified geographic area or system.
-
E.
subwayServices
Indicates that one entity provides or operates subway transportation services for another entity or area.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec05ec4c8190bd5e5463163712dc |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.