Triple
T34508202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Mary Cray railway station |
E885944
|
entity |
| Predicate | distanceFromLondonBlackfriars |
P205449
|
FINISHED |
| Object | approximately 14 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 14 miles | Statement: [St Mary Cray railway station, distanceFromLondonBlackfriars, approximately 14 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLondonBlackfriars Context triple: [St Mary Cray railway station, distanceFromLondonBlackfriars, approximately 14 miles]
-
A.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
B.
distanceFromLiverpoolStreet
Indicates the measured distance between a given location and Liverpool Street.
-
C.
distanceFromBakerStreet
Indicates the measured spatial distance between a given entity and Baker Street.
-
D.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
E.
distanceToBuckingham
Indicates the spatial distance between a given entity and Buckingham (e.g., Buckingham Palace or the locality named Buckingham).
- 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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 2:01 a.m.