Triple
T6926789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bury Metrolink line |
E160330
|
entity |
| Predicate | openedAsMetrolinkLine |
P73705
|
FINISHED |
| Object | 1992 |
—
|
LITERAL 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: 1992 | Statement: [Bury Metrolink line, openedAsMetrolinkLine, 1992]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedAsMetrolinkLine Context triple: [Bury Metrolink line, openedAsMetrolinkLine, 1992]
-
A.
openedAsMetrolinkStop
Indicates that a location began operation specifically as a Metrolink transit stop.
-
B.
openedAsRedLineStation
Indicates that a station began operation specifically as part of the Red Line when it first opened.
-
C.
openedAsSubway
Indicates that a transportation facility or line originally began operation specifically as a subway service.
-
D.
openedAsMetroNorthService
Indicates that a transportation facility or line began operation specifically as part of the Metro-North Railroad service.
-
E.
hasMetroLine
Indicates that a location or area is served by, or connected to, a specific metro (subway) line.
- F. None of above. chosen
Provenance (4 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da1aa9c48190b63a04be2ed9e266 |
completed | March 27, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bb577c81908ee8b415b4281f3d |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d98625c88190a37fdf6d95d7fcbd |
completed | March 27, 2026, 7:24 p.m. |
Created at: March 27, 2026, 2:27 p.m.