Triple
T626541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (CTA) |
E15830
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object |
Lake
Lake is a Chicago Transit Authority 'L' station in the Loop that serves the Red Line subway.
|
E86833
|
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: Lake | Statement: [Red Line (CTA), servesStation, Lake]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Context triple: [Red Line (CTA), servesStation, Lake]
-
A.
The Lake
The Lake is a village-like neighborhood in Newton, Massachusetts, known for its strong community identity and historically Irish-American roots.
-
B.
The Lake
The Lake is a picturesque man-made body of water in New York City's Central Park, popular for boating, scenic views, and surrounding walking paths.
-
C.
Simly Lake
Simly Lake is a major freshwater reservoir and popular recreational spot located in the Margalla Hills near Islamabad, Pakistan.
-
D.
Great Lake
The Great Lake is an expansive ornamental body of water forming a dramatic focal point within the landscaped grounds of Blenheim Palace in Oxfordshire, England.
-
E.
Lake Carnegie
Lake Carnegie is a man-made lake in Princeton, New Jersey, best known as a rowing and recreational waterway associated with Princeton University.
- 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: Lake Triple: [Red Line (CTA), servesStation, Lake]
Generated description
Lake is a Chicago Transit Authority 'L' station in the Loop that serves the Red Line subway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lake Target entity description: Lake is a Chicago Transit Authority 'L' station in the Loop that serves the Red Line subway.
-
A.
The Lake
The Lake is a village-like neighborhood in Newton, Massachusetts, known for its strong community identity and historically Irish-American roots.
-
B.
The Lake
The Lake is a picturesque man-made body of water in New York City's Central Park, popular for boating, scenic views, and surrounding walking paths.
-
C.
Simly Lake
Simly Lake is a major freshwater reservoir and popular recreational spot located in the Margalla Hills near Islamabad, Pakistan.
-
D.
Great Lake
The Great Lake is an expansive ornamental body of water forming a dramatic focal point within the landscaped grounds of Blenheim Palace in Oxfordshire, England.
-
E.
Lake Carnegie
Lake Carnegie is a man-made lake in Princeton, New Jersey, best known as a rowing and recreational waterway associated with Princeton University.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e587c448190987943a6aad209d1 |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a63742d8a8819087c7c2fa2430da75 |
completed | March 3, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_69a637ef099c8190a23f59a39e4e110a |
completed | March 3, 2026, 1:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a63c075f988190aa9f7073b44fb97b |
completed | March 3, 2026, 1:40 a.m. |
Created at: March 1, 2026, 7:35 p.m.