Triple
T1902180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Cannon Street |
E37712
|
entity |
| Predicate | stationUsage |
P27765
|
FINISHED |
| Object | primarily weekday commuter traffic |
—
|
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: primarily weekday commuter traffic | Statement: [London Cannon Street, stationUsage, primarily weekday commuter traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationUsage Context triple: [London Cannon Street, stationUsage, primarily weekday commuter traffic]
-
A.
stationType
chosen
Indicates the specific category or classification of a station based on its function, services, or operational characteristics.
-
B.
stationComplex
Indicates a relationship where one entity is a station complex that encompasses or is associated with another station-related entity.
-
C.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
D.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
-
E.
servesAsThroughStationFor
Indicates that a station functions as an intermediate (through) stop for a particular service, route, or journey rather than as its starting or ending point.
- 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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafe9f8b0819086d8f6288511c66d |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.