Triple
T9813333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Line C Branch |
E238333
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | North Station |
E2878
|
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: North Station | Statement: [Green Line C Branch, terminus, North Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: North Station Context triple: [Green Line C Branch, terminus, North Station]
-
A.
North Station
chosen
North Station is a major transportation hub in Boston, Massachusetts, serving as a key commuter rail, subway, and intercity bus terminal integrated with the TD Garden arena.
-
B.
North Station
North Station is a passenger stop on Detroit Metropolitan Airport’s McNamara Terminal ExpressTram, serving travelers moving along the terminal concourse.
-
C.
Airport North Station
Airport North Station is a metro station in Shenzhen that serves the Shenzhen Bao’an International Airport area, providing urban rail access for air travelers and airport staff.
-
D.
Airport North Station
Airport North Station is a Guangzhou Metro station serving the northern area of Guangzhou Baiyun International Airport.
-
E.
South Station
South Station is Boston’s major intercity rail and bus terminal and a key MBTA subway hub in the city’s downtown.
- 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_69ca84defac48190abc1148804f184c1 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb22410208190b82b81a4df800f80 |
completed | April 2, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc63c450819091e57030a48e7d88 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:30 p.m.