Triple
T5853005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wernigerode |
E130080
|
entity |
| Predicate | hasOldTownFeature |
P6684
|
FINISHED |
| Object | market square |
—
|
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: market square | Statement: [Wernigerode, hasOldTownFeature, market square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOldTownFeature Context triple: [Wernigerode, hasOldTownFeature, market square]
-
A.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
B.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
C.
hasTopFloorFeature
Indicates that a building’s top floor possesses a specific feature, attribute, or amenity.
-
D.
hasArchitecturalFeature
chosen
Indicates that one entity possesses, includes, or is characterized by a specific architectural feature or element.
-
E.
hasNewTown
Indicates that an entity is associated with, or has established, a newly created town.
- 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_69c0084de39081909eb34e6bed74215a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03345ca0c819081c81148d054fed2 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.