Triple
T20301934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Line (MBTA) |
E505502
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Brighton |
—
|
NE NERFINISHED |
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: Brighton | Statement: [Green Line (MBTA), serves, Brighton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brighton Context triple: [Green Line (MBTA), serves, Brighton]
-
A.
Brighton
chosen
Brighton is a residential neighborhood in the western part of Boston, Massachusetts, known for its mix of students, young professionals, and long-time residents.
-
B.
Brighton
Brighton is a major seaside city on England’s south coast, renowned for its beach, pier, and vibrant cultural and nightlife scenes.
-
C.
Brighton
Brighton is a small city in Colorado that forms part of the Denver metropolitan area along the Front Range of the Rocky Mountains.
-
D.
Brighton
Brighton is a small mountain resort town in Utah known for its ski area, alpine scenery, and outdoor recreation.
-
E.
Brighton
Brighton is a small municipality in southeastern Ontario, Canada, known for its rural charm, proximity to Lake Ontario, and nearby Presqu’ile Provincial Park.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770d82b48190b21ce7c52ec6d5a0 |
completed | April 20, 2026, 6:57 p.m. |
Created at: April 16, 2026, 11:17 a.m.