Triple
T187950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Shore Limited |
E4023
|
entity |
| Predicate | trainNumberDirection |
P5681
|
FINISHED |
| Object | 48 eastbound Chicago to New York |
—
|
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: 48 eastbound Chicago to New York | Statement: [Lake Shore Limited, trainNumberDirection, 48 eastbound Chicago to New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainNumberDirection Context triple: [Lake Shore Limited, trainNumberDirection, 48 eastbound Chicago to New York]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
C.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
D.
hasTrafficDirection
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
E.
trafficDirection
Indicates the direction in which traffic is intended or allowed to move relative to a given reference point or segment.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594940e48190a3d8efbce46241c3 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25672332081909386f35f3ca15dd2 |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a25738b5108190866fd704fceee18a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.