Triple
T6448673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Jervis Line |
E139807
|
entity |
| Predicate | primaryStation |
P394
|
FINISHED |
| Object |
Tuxedo station
Tuxedo station is a commuter rail stop in Tuxedo, New York, serving passengers on the Port Jervis Line between New York City and Orange County.
|
E596021
|
NE FINISHED |
How this triple was built (4 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: Tuxedo station | Statement: [Port Jervis Line, primaryStation, Tuxedo station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tuxedo station Context triple: [Port Jervis Line, primaryStation, Tuxedo station]
-
A.
Patterson station
Patterson station is a commuter rail stop in Patterson, New York, served by the Metro-North Railroad on its Harlem Line.
-
B.
Snyder station
Snyder station is an underground rapid transit stop on SEPTA’s Broad Street Line serving South Philadelphia.
-
C.
Dorsey station
Dorsey station is a commuter rail stop in Maryland served by MARC’s Camden Line between Washington, D.C., and Baltimore.
-
D.
Stadium Station
Stadium Station is a light rail station in Seattle’s SoDo neighborhood that primarily serves the nearby sports stadiums and industrial area.
-
E.
Atco station
Atco station is a New Jersey Transit rail stop in Atco, New Jersey, serving passengers on the Atlantic City Line between Philadelphia and Atlantic City.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tuxedo station Triple: [Port Jervis Line, primaryStation, Tuxedo station]
Generated description
Tuxedo station is a commuter rail stop in Tuxedo, New York, serving passengers on the Port Jervis Line between New York City and Orange County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tuxedo station Target entity description: Tuxedo station is a commuter rail stop in Tuxedo, New York, serving passengers on the Port Jervis Line between New York City and Orange County.
-
A.
Patterson station
Patterson station is a commuter rail stop in Patterson, New York, served by the Metro-North Railroad on its Harlem Line.
-
B.
Snyder station
Snyder station is an underground rapid transit stop on SEPTA’s Broad Street Line serving South Philadelphia.
-
C.
Dorsey station
Dorsey station is a commuter rail stop in Maryland served by MARC’s Camden Line between Washington, D.C., and Baltimore.
-
D.
Stadium Station
Stadium Station is a light rail station in Seattle’s SoDo neighborhood that primarily serves the nearby sports stadiums and industrial area.
-
E.
Atco station
Atco station is a New Jersey Transit rail stop in Atco, New Jersey, serving passengers on the Atlantic City Line between Philadelphia and Atlantic City.
- F. None of above. chosen
Provenance (5 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_69c008b301948190a35854e5284dc822 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069b1a61c81908610264c098d25b0 |
completed | March 22, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65392a6c08190b868fab12260d6c2 |
completed | March 27, 2026, 9:53 a.m. |
| NEDg | Description generation | batch_69c6553c17bc81908719ecc7db9e3960 |
completed | March 27, 2026, 10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c655f4ee5c81909620e732b72ee694 |
completed | March 27, 2026, 10:03 a.m. |
Created at: March 22, 2026, 4:47 p.m.