Triple
T187930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Shore Limited |
E4023
|
entity |
| Predicate | via |
P5680
|
FINISHED |
| Object | Buffalo |
E22106
|
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: Buffalo | Statement: [Lake Shore Limited, via, Buffalo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buffalo Context triple: [Lake Shore Limited, via, Buffalo]
-
A.
Buffalo
chosen
Buffalo is a major city in western New York State known for its industrial history, proximity to Niagara Falls, and namesake Buffalo-style chicken wings.
-
B.
Rochester
Rochester is a major city in western New York State known historically for its role in industry, photography, and social reform movements.
-
C.
Syracuse
Syracuse is a mid-sized city in central New York State known for Syracuse University, its role as a regional economic and cultural hub, and its snowy winters.
-
D.
Albany
Albany is the capital city of the U.S. state of New York, known as a historic political and cultural center in the northeastern United States.
-
E.
Canton
Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bc834388190a93ec1ab0d5946de |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a481e765b88190a96eb2d5aa108a11 |
completed | March 1, 2026, 6:13 p.m. |
Created at: Feb. 28, 2026, 2:40 a.m.