Triple
T12724975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnos Grove |
E304080
|
entity |
| Predicate | fareZoneFromCentralLondon |
P106587
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Arnos Grove, fareZoneFromCentralLondon, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareZoneFromCentralLondon Context triple: [Arnos Grove, fareZoneFromCentralLondon, 4]
-
A.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
B.
hasAdjacentStationAwayFromCentralLondon
Indicates that an entity (such as a station) has a neighboring station that is located outside the central London area.
-
C.
hasAdjacentStationTowardsCentralLondon
Indicates that one station has a neighboring station located in the direction of central London along a transit route.
-
D.
fareZoneIncludes
Indicates that a specified fare zone geographically or logically contains a given location, stop, or segment for fare calculation purposes.
-
E.
withinLondonCommuterBelt
Indicates that a location lies within the geographic area from which people commonly commute into London for work or study.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96403957c81909acdee7bdae71696 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:25 p.m.