Triple
T1376706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reading Terminal complex |
E29241
|
entity |
| Predicate | railwayStationFor |
P27112
|
FINISHED |
| Object | Reading Company passenger trains |
—
|
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: Reading Company passenger trains | Statement: [Reading Terminal complex, railwayStationFor, Reading Company passenger trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayStationFor Context triple: [Reading Terminal complex, railwayStationFor, Reading Company passenger trains]
-
A.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
B.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
C.
railroadTerminusFor
Indicates that one location serves as the end point or final station of a particular railroad line for another location.
-
D.
stationName
Indicates the name assigned to a particular station in the relationship.
-
E.
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.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2f9b51c8190ad52fd8c151499be |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0335f7081908d50046ced4cdee0 |
completed | March 1, 2026, 10:39 p.m. |
Created at: March 1, 2026, 7:59 p.m.