Triple
T28818823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brand-Erbisdorf |
E727703
|
entity |
| Predicate | distanceToFreiberg |
P202021
|
FINISHED |
| Object | approximately 5 km south |
—
|
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 5 km south | Statement: [Brand-Erbisdorf, distanceToFreiberg, approximately 5 km south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToFreiberg Context triple: [Brand-Erbisdorf, distanceToFreiberg, approximately 5 km south]
-
A.
distanceToZwickau
Indicates the measured spatial distance between a given entity and the location of Zwickau.
-
B.
distanceToCottbus
Indicates the spatial distance between an entity and the location Cottbus.
-
C.
distanceToDresden
Indicates the spatial distance between a given entity or location and the city of Dresden.
-
D.
distanceToErfurt
Indicates the spatial distance between a given location or entity and the city of Erfurt.
-
E.
distanceFromEsbjerg
Indicates the measured or specified distance between a given entity or location and the city of Esbjerg.
- 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_69f0319d09088190bbf14cdf1987792a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_6a00474f08908190bc8ae3b320ec887b |
completed | May 10, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_6a0045dc3bd48190a9e0520f3ef3f067 |
completed | May 10, 2026, 8:46 a.m. |
| PDg | Predicate description generation | batch_6a00474e552c8190b711363081d29292 |
completed | May 10, 2026, 8:52 a.m. |
Created at: April 28, 2026, 6:33 a.m.