Triple
T8134400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Line (DART) |
E189932
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Cedars station
Cedars station is a light rail stop on Dallas Area Rapid Transit’s Green Line serving the Cedars neighborhood just south of downtown Dallas, Texas.
|
E720247
|
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: Cedars station | Statement: [Green Line (DART), hasStation, Cedars station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cedars station Context triple: [Green Line (DART), hasStation, Cedars station]
-
A.
Meadowview Station
Meadowview Station is a light rail transit station in Sacramento, California, serving as part of the Sacramento Regional Transit District’s network.
-
B.
Kedzie station
Kedzie station is a Chicago 'L' rapid transit stop on the Brown Line serving the city's Northwest Side.
-
C.
Crestmont station
Crestmont station is a SEPTA Regional Rail stop in Abington Township, Pennsylvania, serving passengers on the Warminster Line.
-
D.
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.
-
E.
Edgewood station
Edgewood station is a commuter rail stop in Edgewood, Maryland, served by MARC’s Penn Line between Baltimore and Perryville.
- 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: Cedars station Triple: [Green Line (DART), hasStation, Cedars station]
Generated description
Cedars station is a light rail stop on Dallas Area Rapid Transit’s Green Line serving the Cedars neighborhood just south of downtown Dallas, Texas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cedars station Target entity description: Cedars station is a light rail stop on Dallas Area Rapid Transit’s Green Line serving the Cedars neighborhood just south of downtown Dallas, Texas.
-
A.
Meadowview Station
Meadowview Station is a light rail transit station in Sacramento, California, serving as part of the Sacramento Regional Transit District’s network.
-
B.
Kedzie station
Kedzie station is a Chicago 'L' rapid transit stop on the Brown Line serving the city's Northwest Side.
-
C.
Crestmont station
Crestmont station is a SEPTA Regional Rail stop in Abington Township, Pennsylvania, serving passengers on the Warminster Line.
-
D.
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.
-
E.
Edgewood station
Edgewood station is a commuter rail stop in Edgewood, Maryland, served by MARC’s Penn Line between Baltimore and Perryville.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb43bbae608190bdc1afe6f0ab83ae |
completed | March 31, 2026, 3:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3457196081909f739af8c17b4d4c |
completed | April 1, 2026, 3:05 p.m. |
| NEDg | Description generation | batch_69cd36ecc1d88190a978f1d51b0e1382 |
completed | April 1, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd4e9d362481908283d58b03c7ef9b |
completed | April 1, 2026, 4:58 p.m. |
Created at: March 30, 2026, 5:35 p.m.