Triple
T26869367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kearsney |
E676565
|
entity |
| Predicate | distanceToDoverTownCentre |
P33782
|
FINISHED |
| Object | approximately 2 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 2 miles | Statement: [Kearsney, distanceToDoverTownCentre, approximately 2 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDoverTownCentre Context triple: [Kearsney, distanceToDoverTownCentre, approximately 2 miles]
-
A.
distanceFromDover
chosen
Indicates the measured distance between a given entity or location and the place named Dover.
-
B.
distanceToChesterCityCentre
Indicates the measured or specified distance between a given location and the centre of Chester city.
-
C.
distanceToYorkCityCentre
Indicates the measured or specified distance between a given location and the centre of York city.
-
D.
distanceToBradfordCityCentre
Indicates the spatial distance between a given location and the centre of Bradford city.
-
E.
distanceToHunstanton
Indicates the measured spatial distance between a given entity and the location Hunstanton.
- 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_69eee9ba94bc8190b44c5d4397d04ecd |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fedd5a5f4c8190acce88db56303703 |
completed | May 9, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69fed910b31c8190ae837163d146738d |
completed | May 9, 2026, 6:49 a.m. |
Created at: April 27, 2026, 5:31 a.m.