Triple
T12754788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groton, South Dakota |
E304828
|
entity |
| Predicate | distanceToAberdeenApprox |
P28185
|
FINISHED |
| Object | about 20 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: about 20 miles southeast | Statement: [Groton, South Dakota, distanceToAberdeenApprox, about 20 miles southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAberdeenApprox Context triple: [Groton, South Dakota, distanceToAberdeenApprox, about 20 miles southeast]
-
A.
distanceToAberdeen
chosen
Indicates the spatial distance between a given entity and the location of Aberdeen.
-
B.
distanceToAyr
Indicates the measured distance between a given entity or location and Ayr.
-
C.
directionFromAberdeen
Indicates the directional relationship of one place or object as measured outward starting from Aberdeen.
-
D.
distanceToInverness
Indicates the spatial distance between a given entity and the location of Inverness.
-
E.
distanceToDundee
Indicates the measured spatial distance between a given entity and the location of Dundee.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.