Triple
T12500985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chalfont & Latimer |
E298819
|
entity |
| Predicate | distanceFromBakerStreet |
P105315
|
FINISHED |
| Object | approximately 21 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 21 miles | Statement: [Chalfont & Latimer, distanceFromBakerStreet, approximately 21 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBakerStreet Context triple: [Chalfont & Latimer, distanceFromBakerStreet, approximately 21 miles]
-
A.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
B.
distanceToBuckingham
Indicates the spatial distance between a given entity and Buckingham (e.g., Buckingham Palace or the locality named Buckingham).
-
C.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
D.
distanceFromStPancras
Indicates the spatial distance between an entity and St Pancras.
-
E.
distanceToYorkCityCentre
Indicates the measured or specified distance between a given location and the centre of York city.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e87e0e88190bc49dcfe4954c7e0 |
completed | April 10, 2026, 7:24 p.m. |
Created at: April 8, 2026, 9:57 p.m.