Triple
T12835851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fair Park station |
E306909
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object |
Green Line
The Green Line is a public transit rail route that serves stations such as Fair Park within its metropolitan network.
|
E189932
|
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: Green Line | Statement: [Fair Park station, servedByLine, Green Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green Line Context triple: [Fair Park station, servedByLine, Green Line]
-
A.
Green Line
The Green Line is one of Chicago's elevated rapid transit routes, running primarily along the city's West and South Sides as part of the Chicago "L" system.
-
B.
Green Line
The Green Line was the former name of Los Angeles Metro's C Line, a light rail route serving the South Bay region and connecting to LAX via nearby stations.
-
C.
Green Line
The Green Line is a light rail service route within the San Diego Trolley system that connects key destinations across the San Diego metropolitan area.
-
D.
Green Line
The Green Line is a light rail service operated as part of Cleveland's RTA Rapid Transit system.
-
E.
Green Line
The Green Line is one of the main light rail routes of Dublin’s Luas tram system, serving key suburbs and city areas along its corridor.
- 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: Green Line Triple: [Fair Park station, servedByLine, Green Line]
Generated description
The Green Line is a public transit rail route that serves stations such as Fair Park within its metropolitan network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Green Line Target entity description: The Green Line is a public transit rail route that serves stations such as Fair Park within its metropolitan network.
-
A.
Green Line
The Green Line is one of the light rail routes in Houston’s METRORail system, serving the city’s East End and connecting it to downtown.
-
B.
Green Line
chosen
The Green Line is a light rail route in Dallas, Texas, operated by Dallas Area Rapid Transit (DART), running through key areas including downtown and connecting several suburbs.
-
C.
Green Line
The Green Line is a public transit route, likely part of an urban rail or metro system, that intersects with the Purple Line Express.
-
D.
Green Line
The Green Line is a light rail service within Salt Lake City's TRAX system that connects key destinations across the metropolitan area.
-
E.
Green Line
The Green Line is a rapid transit route within Miami-Dade County's Metrorail system, providing north-south rail service through key urban neighborhoods and connections.
- F. None of above.
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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff015f4819090070a01f3938acc |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a54838888190804202e45a55de48 |
completed | May 3, 2026, 1:30 a.m. |
| NEDg | Description generation | batch_69f6a616f6e4819096c9850434882548 |
completed | May 3, 2026, 1:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6a716bb2c81909dccc5ddbf3c92b5 |
completed | May 3, 2026, 1:38 a.m. |
Created at: April 9, 2026, 5:35 p.m.