Triple
T10186312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London fare zone 4 |
E236917
|
entity |
| Predicate | fareLevelComparedToZone1 |
P92593
|
FINISHED |
| Object | cheaper |
—
|
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: cheaper | Statement: [London fare zone 4, fareLevelComparedToZone1, cheaper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareLevelComparedToZone1 Context triple: [London fare zone 4, fareLevelComparedToZone1, cheaper]
-
A.
fareZoneIncludes
Indicates that a specified fare zone geographically or logically contains a given location, stop, or segment for fare calculation purposes.
-
B.
fareZoneHierarchyPosition
Indicates the relative level or rank of a fare zone within a hierarchical fare zone structure.
-
C.
fareZoneUsage
Indicates how a fare zone is applied or utilized within a transportation or pricing context.
-
D.
fareSystem
Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
-
E.
fareType
Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded790b488190b1ed4645554873cd |
completed | April 2, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69cd7edc6cf081909d95859d880a4059 |
completed | April 1, 2026, 8:23 p.m. |
Created at: March 30, 2026, 9:12 p.m.