Triple
T19446721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crossharbour DLR Station |
E486495
|
entity |
| Predicate | hasOysterCardFacility |
P135505
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Crossharbour DLR Station, hasOysterCardFacility, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOysterCardFacility Context triple: [Crossharbour DLR Station, hasOysterCardFacility, yes]
-
A.
hasOysterCardReaders
chosen
Indicates that the subject is equipped with or contains Oyster card readers for validating or processing Oyster card transactions.
-
B.
isWithinLondonFareSystem
Indicates that an entity (such as a station, stop, or route) is located inside the area covered by the London public transport fare system.
-
C.
hasOpalCardReaders
Indicates that an entity is equipped with or contains Opal card readers for processing Opal transit card transactions.
-
D.
endStationProvidesAccessTo
Indicates that a particular end station offers access or connectivity to another location, service, or network resource.
-
E.
isWithinFareSystem
Indicates that one transportation service, route, or area operates under and is covered by a specified fare or ticketing system.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338a22608190bb31a1690ca0dab6 |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.