Triple
T35574786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilvesheim |
E1028044
|
entity |
| Predicate | distanceToMannheimCityCentre |
P207054
|
FINISHED |
| Object | approximately 5 kilometres |
—
|
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 kilometres | Statement: [Ilvesheim, distanceToMannheimCityCentre, approximately 5 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMannheimCityCentre Context triple: [Ilvesheim, distanceToMannheimCityCentre, approximately 5 kilometres]
-
A.
distanceFromMainzHbf
Indicates the spatial distance between an entity and Mainz Hauptbahnhof (Mainz central railway station).
-
B.
distanceToBonnCentre
Indicates the spatial distance between a given location and the center of Bonn.
-
C.
distanceFromDarmstadtHbf
Indicates the spatial distance between a given location and Darmstadt Hauptbahnhof (Darmstadt central railway station).
-
D.
distanceToWiesbaden
Indicates the spatial distance between a given entity or location and the city of Wiesbaden.
-
E.
distanceToMunich
Indicates the spatial distance between a given entity’s location and the city of Munich.
- 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_69f76e0386688190b931bacdc145938c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.