Triple
T4819388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White River Junction, Vermont |
E107670
|
entity |
| Predicate | majorRailJunctionSince |
P38623
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [White River Junction, Vermont, majorRailJunctionSince, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorRailJunctionSince Context triple: [White River Junction, Vermont, majorRailJunctionSince, 19th century]
-
A.
railwayJunctionFor
Indicates that a location serves as a junction point where multiple railway lines or routes connect or intersect for a given railway network or service.
-
B.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
-
C.
railwaySignificance
chosen
Indicates the importance or role that a railway or rail-related feature has within a transportation network, region, or context.
-
D.
usesRailInfrastructureOf
Indicates that one entity operates on, accesses, or otherwise makes use of the rail infrastructure owned or managed by another entity.
-
E.
railInterface
Indicates a connection or interaction between entities via a rail-based system or interface.
- F. None of above.
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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.