Triple
T70000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pittsburgh region |
E1400
|
entity |
| Predicate | transportationHubFor |
P2413
|
FINISHED |
| Object | rail freight |
—
|
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: rail freight | Statement: [Pittsburgh region, transportationHubFor, rail freight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportationHubFor Context triple: [Pittsburgh region, transportationHubFor, rail freight]
-
A.
hasTransportHub
chosen
Indicates that a location contains or serves as a central facility where multiple transport routes or modes connect for passenger or cargo movement.
-
B.
transportCorridor
Indicates a route or pathway used to move people, goods, or resources between locations.
-
C.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
D.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
E.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.