Triple
T18786338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chorleywood railway station |
E459385
|
entity |
| Predicate | distanceFromLondonBakerStreet |
P105315
|
FINISHED |
| Object | approximately 23 miles |
—
|
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: approximately 23 miles | Statement: [Chorleywood railway station, distanceFromLondonBakerStreet, approximately 23 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLondonBakerStreet Context triple: [Chorleywood railway station, distanceFromLondonBakerStreet, approximately 23 miles]
-
A.
distanceFromBakerStreet
chosen
Indicates the measured spatial distance between a given entity and Baker Street.
-
B.
distanceFromLiverpoolStreet
Indicates the measured distance between a given location and Liverpool Street.
-
C.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
D.
distanceToBuckingham
Indicates the spatial distance between a given entity and Buckingham (e.g., Buckingham Palace or the locality named Buckingham).
-
E.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5978154ac819096356d2a488b45f0 |
completed | April 20, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.