Triple
T21650733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martinsried |
E534329
|
entity |
| Predicate | distanceToMunichCenter |
P84034
|
FINISHED |
| Object | approximately 10 kilometers |
—
|
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 10 kilometers | Statement: [Martinsried, distanceToMunichCenter, approximately 10 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMunichCenter Context triple: [Martinsried, distanceToMunichCenter, approximately 10 kilometers]
-
A.
distanceToMunich
chosen
Indicates the spatial distance between a given entity’s location and the city of Munich.
-
B.
roadDistanceToCityCentre_km
Indicates the distance in kilometers from a location to the city centre when traveling by road.
-
C.
directionFromCityCenter
Indicates the compass direction in which one location lies relative to the city center.
-
D.
distanceToKoblenz
Indicates the spatial distance between a given entity and the location of Koblenz.
-
E.
distanceToRosenheim
Indicates the spatial distance between a given entity and the location Rosenheim.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5913cd9c81908a6ce9bc741416bf |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:35 p.m.