Triple
T13112388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schlettstadt |
E311003
|
entity |
| Predicate | hasMedievalUrbanLayout |
P29116
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Schlettstadt, hasMedievalUrbanLayout, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedievalUrbanLayout Context triple: [Schlettstadt, hasMedievalUrbanLayout, yes]
-
A.
hasMedievalStreetPattern
chosen
Indicates that an area’s street layout follows or preserves a characteristic medieval pattern of routes, blocks, and spaces.
-
B.
hasColonialUrbanLayout
Indicates that an urban area’s spatial organization and street pattern follow a design imposed during a colonial period, reflecting colonial planning principles and control.
-
C.
majorMedievalCity
Indicates that a location was a significant and influential urban center during the medieval period.
-
D.
hasUrbanLayoutType
Indicates that an entity possesses or is characterized by a specific type or pattern of urban spatial layout.
-
E.
hasPlannedUrbanCharacter
Indicates that an area exhibits an intentionally designed and organized urban form, layout, and land use pattern rather than informal or unplanned development.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817f8ee8819084078b4bec5e4f18 |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98041a3548190a05ddd83dbb660fa |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:05 p.m.