Triple
T5616219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wassaic Branch |
E147483
|
entity |
| Predicate | openedAsMetroNorthService |
P64668
|
FINISHED |
| Object | 2000 |
—
|
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: 2000 | Statement: [Wassaic Branch, openedAsMetroNorthService, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedAsMetroNorthService Context triple: [Wassaic Branch, openedAsMetroNorthService, 2000]
-
A.
openedAsPartOfNJTransit
Indicates that the subject entity was opened specifically as a component or facility of the NJ Transit system.
-
B.
openedAsSubway
Indicates that a transportation facility or line originally began operation specifically as a subway service.
-
C.
openedAsMBTAStation
Indicates that an entity began operation specifically as an MBTA station at a particular time.
-
D.
openedAsMetrolinkStop
Indicates that a location began operation specifically as a Metrolink transit stop.
-
E.
openedAsRERStation
Indicates that a station began operation specifically as part of the RER (Réseau Express Régional) network from its opening date.
- 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_69c00905d4588190bd967842bbcf2219 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c021da7f848190bb1cd0270ad6398f |
completed | March 22, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:39 p.m.