Triple
T23160602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epsom to London Bridge route |
E578569
|
entity |
| Predicate | hasTerminusStationType |
P77457
|
FINISHED |
| Object | major London terminal |
—
|
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: major London terminal | Statement: [Epsom to London Bridge route, hasTerminusStationType, major London terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerminusStationType Context triple: [Epsom to London Bridge route, hasTerminusStationType, major London terminal]
-
A.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
-
B.
hasEndpointStation
Indicates that something (such as a route, line, or service) has a specific station as one of its terminal endpoints.
-
C.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
D.
hasStationTypeAt
Indicates that a specific type of station is present or assigned at a particular location or point.
-
E.
passengerTerminalType
chosen
Indicates the specific kind or category of passenger terminal associated with an entity.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f006930819097aafef87405d737 |
completed | April 29, 2026, 4:54 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:02 p.m.