Triple
T8910799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zone 1 |
E212175
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object | Travelcard |
E59709
|
NE 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: Travelcard | Statement: [Zone 1, fareSystem, Travelcard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Travelcard Context triple: [Zone 1, fareSystem, Travelcard]
-
A.
Travelcard
chosen
Travelcard is a ticketing product used across London’s public transport network, allowing unlimited travel within selected zones on services such as the Underground, buses, and trains.
-
B.
Travelcard Zone 9
Travelcard Zone 9 is one of the outermost London fare zones, covering certain suburban and out-of-London railway stations for Travelcard and contactless ticketing.
-
C.
Travelcard Zone 6
Travelcard Zone 6 is one of the outer fare zones in the London public transport system, covering suburban areas on the edge of Greater London.
-
D.
System One travelcards
System One travelcards are integrated public transport tickets in Greater Manchester that allow unlimited travel across multiple operators and modes within selected zones.
-
E.
Travelcard Zone 3
Travelcard Zone 3 is a ring of suburban areas in London used for calculating fares on public transport services such as the Underground, Overground, and buses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8393b1808190bd4336787ffa2c40 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6523b9348190a7cefac9e73e2004 |
completed | April 1, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba36f8cc8190ab57ddc99b7219d1 |
completed | April 3, 2026, 1:01 p.m. |
Created at: March 30, 2026, 6:55 p.m.