Triple
T14477394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spilsby, Lincolnshire, England |
E359007
|
entity |
| Predicate | distanceToSkegness |
P114802
|
FINISHED |
| Object | about 12 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: about 12 miles | Statement: [Spilsby, Lincolnshire, England, distanceToSkegness, about 12 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSkegness Context triple: [Spilsby, Lincolnshire, England, distanceToSkegness, about 12 miles]
-
A.
distanceFromArendal
Indicates the spatial distance between a given entity and the location of Arendal.
-
B.
distanceFromKristiansand
Indicates the spatial distance between a given location or object and the city of Kristiansand.
-
C.
distanceFromLongyearbyen
Indicates the measured distance between a given location and Longyearbyen.
-
D.
distanceToFlensburg_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Flensburg.
-
E.
distanceFromCopenhagen
Indicates the spatial distance between a given entity and the location of Copenhagen.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9248edb48190a74eb032aeaac027 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de610330a48190b558235a14c0dc9f |
completed | April 14, 2026, 3:45 p.m. |
Created at: April 10, 2026, 1:20 a.m.