Triple
T27280006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mespelbrunn |
E688303
|
entity |
| Predicate | distanceToWuerzburg |
P199101
|
FINISHED |
| Object | about 80 kilometres northwest |
—
|
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 80 kilometres northwest | Statement: [Mespelbrunn, distanceToWuerzburg, about 80 kilometres northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToWuerzburg Context triple: [Mespelbrunn, distanceToWuerzburg, about 80 kilometres northwest]
-
A.
distanceToMunich
Indicates the spatial distance between a given entity’s location and the city of Munich.
-
B.
distanceToWetzlar
Indicates the measured distance between a given entity or location and the place named Wetzlar.
-
C.
distanceToStuttgart
Indicates the measured distance between a given entity’s location and the city of Stuttgart.
-
D.
distanceToWiesbaden
Indicates the spatial distance between a given entity or location and the city of Wiesbaden.
-
E.
distanceToErfurt
Indicates the spatial distance between a given location or entity and the city of Erfurt.
- 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_69ef3558cf8881909595ef89daf6e14a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69ff1f3f94fc819095955299f50ab4ce |
completed | May 9, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69ff1ea47748819082f63d9b9d9c3e65 |
completed | May 9, 2026, 11:46 a.m. |
| PDg | Predicate description generation | batch_69ff1f3ee3588190a857d1504c93be8b |
completed | May 9, 2026, 11:49 a.m. |
Created at: April 27, 2026, 11:06 a.m.