Triple
T7327016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southend Central railway station |
E168900
|
entity |
| Predicate | distanceFromLondonFenchurchStreet |
P8256
|
FINISHED |
| Object | approximately 39 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 39 miles | Statement: [Southend Central railway station, distanceFromLondonFenchurchStreet, approximately 39 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLondonFenchurchStreet Context triple: [Southend Central railway station, distanceFromLondonFenchurchStreet, approximately 39 miles]
-
A.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
B.
distanceToLondon
chosen
Indicates the measured distance between a given entity’s location and the city of London.
-
C.
distanceFromStPancras
Indicates the spatial distance between an entity and St Pancras.
-
D.
distanceToYorkCityCentre
Indicates the measured or specified distance between a given location and the centre of York city.
-
E.
distanceToStPaulsCathedral
Indicates the spatial distance between a given entity’s location and St Paul’s Cathedral.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a755e88190a50126e2d1d6d4cb |
completed | March 27, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.