Triple
T6763634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jedburgh |
E154658
|
entity |
| Predicate | distanceToEnglishBorder |
P73340
|
FINISHED |
| Object | about 10 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 10 miles | Statement: [Jedburgh, distanceToEnglishBorder, about 10 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToEnglishBorder Context triple: [Jedburgh, distanceToEnglishBorder, about 10 miles]
-
A.
distanceToCanadianBorder
Indicates the measured or estimated spatial distance between a given location and the nearest point on the Canadian national border.
-
B.
distanceToMexicoBorder
Indicates the measured or estimated distance between a given location or entity and the border of Mexico.
-
C.
distanceToBorder
Indicates the measured or estimated spatial separation between a given entity or location and the nearest relevant border or boundary.
-
D.
distanceToPennsylvaniaBorder
Indicates the measured distance between a given location and the border of Pennsylvania.
-
E.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d3264b7481908816a4d19543fb7b |
completed | March 27, 2026, 6:57 p.m. |
Created at: March 27, 2026, 2:12 p.m.