Triple
T4099622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edmonton LRT |
E87907
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
McEwan Station
McEwan Station is a light rail transit stop on Edmonton’s LRT network in Edmonton, Alberta, Canada.
|
E412793
|
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: McEwan Station | Statement: [Edmonton LRT, hasStation, McEwan Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McEwan Station Context triple: [Edmonton LRT, hasStation, McEwan Station]
-
A.
Waverley Station
Waverley Station is the main railway hub in Edinburgh and one of the busiest and largest train stations in Scotland.
-
B.
Waverley station
Waverley station is a Massachusetts Bay Transportation Authority (MBTA) commuter rail stop in Belmont, Massachusetts, serving the Fitchburg Line.
-
C.
Kipling station
Kipling station is a major western transit hub in Toronto that connects the subway system with regional buses and commuter services.
-
D.
Woodside station
Woodside station is a major Long Island Rail Road commuter rail stop in Queens, New York City, serving as an important transfer point between multiple LIRR branches and New York City Subway lines.
-
E.
Cumming station
Cumming station is an underground stop on Santiago’s Metro network, serving Line 5 in the central area of Chile’s capital city.
- 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: McEwan Station Triple: [Edmonton LRT, hasStation, McEwan Station]
Generated description
McEwan Station is a light rail transit stop on Edmonton’s LRT network in Edmonton, Alberta, Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: McEwan Station Target entity description: McEwan Station is a light rail transit stop on Edmonton’s LRT network in Edmonton, Alberta, Canada.
-
A.
Waverley Station
Waverley Station is the main railway hub in Edinburgh and one of the busiest and largest train stations in Scotland.
-
B.
Waverley station
Waverley station is a Massachusetts Bay Transportation Authority (MBTA) commuter rail stop in Belmont, Massachusetts, serving the Fitchburg Line.
-
C.
Kipling station
Kipling station is a major western transit hub in Toronto that connects the subway system with regional buses and commuter services.
-
D.
Woodside station
Woodside station is a major Long Island Rail Road commuter rail stop in Queens, New York City, serving as an important transfer point between multiple LIRR branches and New York City Subway lines.
-
E.
Cumming station
Cumming station is an underground stop on Santiago’s Metro network, serving Line 5 in the central area of Chile’s capital city.
- 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_69aed94564cc8190a9c1457daedb6e7f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0d9c508190b8aedf83f3310513 |
completed | March 9, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b7585bc81909dc2c02e60a55def |
completed | March 14, 2026, 2:06 p.m. |
| NEDg | Description generation | batch_69b56c3a4b708190a55027fd3b2b76e0 |
completed | March 14, 2026, 2:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b56cc5c704819083dac59bf7b3cb83 |
completed | March 14, 2026, 2:12 p.m. |
Created at: March 9, 2026, 3:40 p.m.