Triple
T686878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roter Turm (Chemnitz) |
E13302
|
entity |
| Predicate | elevationAboveGround |
P221
|
FINISHED |
| Object | approximately 30 metres |
—
|
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 30 metres | Statement: [Roter Turm (Chemnitz), elevationAboveGround, approximately 30 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: elevationAboveGround Context triple: [Roter Turm (Chemnitz), elevationAboveGround, approximately 30 metres]
-
A.
elevation
chosen
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
B.
elevationType
Indicates the kind or classification of elevation associated with an entity, such as how its height or altitude is characterized.
-
C.
elevationAtBase
Indicates the height or altitude measured at the base or lowest point of an object or feature relative to a reference level.
-
D.
typicalElevationRange
Indicates the usual range of elevation values within which something commonly occurs or exists.
-
E.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d2048d48190ab99ab59accb6909 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.