Triple
T3089989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swabia (Bavaria) |
E64457
|
entity |
| Predicate | hasMixedLandscape |
P1895
|
FINISHED |
| Object | industrial cities |
—
|
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: industrial cities | Statement: [Swabia (Bavaria), hasMixedLandscape, industrial cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMixedLandscape Context triple: [Swabia (Bavaria), hasMixedLandscape, industrial cities]
-
A.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
B.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
C.
hasDiverseLandscape
chosen
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
D.
hasPortrait
Indicates that one entity possesses, displays, or is associated with a portrait depicting another entity.
-
E.
hasLandOwnershipMix
Indicates that an entity has a particular combination or distribution of different types of land ownership (e.g., public, private, communal) associated with it.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada20d8f788190b05b8b6b5042bc1a |
completed | March 8, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69ad9ded78f881908be6fc0fb7c35764 |
completed | March 8, 2026, 4:03 p.m. |
Created at: March 8, 2026, 3:03 p.m.