Triple
T8064001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Putney tube station |
E188195
|
entity |
| Predicate | travelcardZoneCombination |
P80296
|
FINISHED |
| Object | Zone 2/3 boundary |
—
|
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: Zone 2/3 boundary | Statement: [East Putney tube station, travelcardZoneCombination, Zone 2/3 boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelcardZoneCombination Context triple: [East Putney tube station, travelcardZoneCombination, Zone 2/3 boundary]
-
A.
fareZoneIncludes
Indicates that a specified fare zone geographically or logically contains a given location, stop, or segment for fare calculation purposes.
-
B.
ticketingZoneType
Indicates the type or category of ticketing zone that applies within a given area or context.
-
C.
continentCombination
Indicates a relationship where multiple continents are grouped or associated together as a combined set or unit.
-
D.
fareZoneUsage
Indicates how a fare zone is applied or utilized within a transportation or pricing context.
-
E.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
- F. None of above. chosen
Provenance (4 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3fd07fd08190a3b61cb3369ee6a6 |
completed | March 31, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69cb049cd51c8190bb3b0f503e42fa8d |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14be17208190bb51c3dfcb613f20 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:26 p.m.