Triple
T2975953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Colney |
E80395
|
entity |
| Predicate | distanceToStAlbans |
P44349
|
FINISHED |
| Object | approximately 3 miles southeast |
—
|
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 3 miles southeast | Statement: [London Colney, distanceToStAlbans, approximately 3 miles southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToStAlbans Context triple: [London Colney, distanceToStAlbans, approximately 3 miles southeast]
-
A.
distanceFromCentralLondon
Indicates the spatial separation or length of travel between a given location and central London.
-
B.
distanceToEgham
Indicates the spatial distance between a given entity and the location of Egham.
-
C.
distanceToLondon
Indicates the measured distance between a given entity’s location and the city of London.
-
D.
distanceFromStirling
Indicates the spatial distance measured from the reference location Stirling to another place or entity.
-
E.
distanceFromLeeds
Indicates the spatial distance between a given entity and the location of Leeds.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad998ad5308190a012ec4940eb46cb |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:58 p.m.