Triple
T7618087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michigan Central Railroad |
E172412
|
entity |
| Predicate | railNetworkConnection |
P24517
|
FINISHED |
| Object | Chicago rail hub |
—
|
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: Chicago rail hub | Statement: [Michigan Central Railroad, railNetworkConnection, Chicago rail hub]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railNetworkConnection Context triple: [Michigan Central Railroad, railNetworkConnection, Chicago rail hub]
-
A.
countryRailConnection
Indicates that there is a railway connection or service linking two countries.
-
B.
hasPassengerRailConnection
Indicates that there exists a passenger rail service linking one location or transport node to another.
-
C.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
D.
railroadNetwork
chosen
Indicates a relationship where locations are connected as part of the same system of railway lines and infrastructure used for train transport.
-
E.
coordinatesRailTrafficWith
Indicates that one entity organizes and synchronizes rail operations or movements with another entity to ensure coordinated train traffic.
- 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_69c699506b308190826894dab1d9ea86 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:55 p.m.