Triple
T17803384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Covent Garden station |
E444490
|
entity |
| Predicate | distanceToLeicesterSquareOnStreet |
P128982
|
FINISHED |
| Object | approximately 300 metres |
—
|
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 300 metres | Statement: [Covent Garden station, distanceToLeicesterSquareOnStreet, approximately 300 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLeicesterSquareOnStreet Context triple: [Covent Garden station, distanceToLeicesterSquareOnStreet, approximately 300 metres]
-
A.
distanceToLeicester
Indicates the spatial distance between a given entity’s location and the location of Leicester.
-
B.
distanceFromBakerStreet
Indicates the measured spatial distance between a given entity and Baker Street.
-
C.
distanceToShaftesbury
Indicates the measured or calculated distance between a given entity and the location named Shaftesbury.
-
D.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4880171608190be2088c7a387bfb7 |
completed | April 19, 2026, 7:45 a.m. |
| PD | Predicate disambiguation | batch_69e3d8de28688190844b65acf6af54e6 |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:13 a.m.