Triple
T25573082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hackbridge railway station |
E641027
|
entity |
| Predicate | isWithinLondonArea |
P75854
|
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: [Hackbridge railway station, isWithinLondonArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWithinLondonArea Context triple: [Hackbridge railway station, isWithinLondonArea, yes]
-
A.
isInInnerLondon
Indicates that one location lies within the administrative area defined as Inner London.
-
B.
hasOuterLondonBorough
Indicates that an entity is associated with, located in, or administered by a borough that is part of Outer London.
-
C.
hasLondonBorough
Indicates that an entity includes, contains, or is associated with a specific London borough as one of its administrative subdivisions.
-
D.
isWithinLondonFareSystem
chosen
Indicates that an entity (such as a station, stop, or route) is located inside the area covered by the London public transport fare system.
-
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.
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_69e75dc281bc819095ec04dc0c3a94d0 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f92daf3081908fa635f62ace1758 |
completed | May 2, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 3:59 p.m.