Triple
T13248812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clock House railway station |
E315473
|
entity |
| Predicate | hasRailDirection |
P15156
|
FINISHED |
| Object | services towards London Cannon Street |
—
|
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: services towards London Cannon Street | Statement: [Clock House railway station, hasRailDirection, services towards London Cannon Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRailDirection Context triple: [Clock House railway station, hasRailDirection, services towards London Cannon Street]
-
A.
railwayTrafficDirection
Indicates the customary side of the track on which trains are operated or expected to run within a given railway system or segment.
-
B.
hasRailRoute
Indicates that there exists a rail-based transportation route or connection between the related entities.
-
C.
hasRouteDirection
chosen
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
-
D.
hasRail
Indicates that something is equipped with, includes, or is connected to a rail or rail system.
-
E.
hasDirectionType
Indicates that something possesses or is associated with a specific type or category of direction.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d9e7ea881908abc4b3a54896692 |
completed | April 10, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69d98bcca7d88190a3e68e99ed3a29e6 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:24 p.m.