Triple
T3556866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTA Brown Line |
E75239
|
entity |
| Predicate | servesNeighborhood |
P82
|
FINISHED |
| Object | Lakeview |
E29184
|
NE 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: Lakeview | Statement: [CTA Brown Line, servesNeighborhood, Lakeview]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakeview Context triple: [CTA Brown Line, servesNeighborhood, Lakeview]
-
A.
Lakeview
Lakeview is a Long Island Rail Road commuter rail station serving the Lakeview neighborhood in Nassau County, New York.
-
B.
Lakeview
chosen
Lakeview is a vibrant North Side Chicago neighborhood known for its lively entertainment scene, lakefront access, and diverse residential areas including Boystown and Wrigleyville.
-
C.
Bayview
Bayview is a subway station on Toronto's Line 4 Sheppard, serving the Bayview Avenue area in North York.
-
D.
Bayview
Bayview is a coastal residential suburb in Darwin, Northern Territory, known for its waterfront homes and proximity to the city centre.
-
E.
Fairview
Fairview is a community in Alameda County, California, situated adjacent to the city of Hayward in the San Francisco Bay Area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc057cc788190a6c4f3781f43abce |
completed | March 8, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bf40dac8190837053dd315303af |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:20 p.m.