Triple
T31350246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moritzburg |
E799568
|
entity |
| Predicate | distanceFromDresden |
P3428
|
FINISHED |
| Object | about 13 kilometers 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 13 kilometers northwest | Statement: [Moritzburg, distanceFromDresden, about 13 kilometers northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDresden Context triple: [Moritzburg, distanceFromDresden, about 13 kilometers northwest]
-
A.
distanceToDresden
chosen
Indicates the spatial distance between a given entity or location and the city of Dresden.
-
B.
distanceToLeipzig
Indicates the spatial distance between a given entity’s location and the city of Leipzig.
-
C.
distanceToZwickau
Indicates the measured spatial distance between a given entity and the location of Zwickau.
-
D.
distanceToChemnitz
Indicates the spatial distance between a given entity or location and the city of Chemnitz.
-
E.
distanceToNuremberg
Indicates the spatial distance between a given entity and the location of Nuremberg.
- 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_69f224e51614819083141459a080e97c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a01c21d8bc481909dd9f5a6b89c0a92 |
completed | May 11, 2026, 11:48 a.m. |
| PD | Predicate disambiguation | batch_6a01bff5d1508190895e5bd2c04932b0 |
completed | May 11, 2026, 11:39 a.m. |
Created at: April 29, 2026, 9:17 p.m.