Triple
T17136589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koňský trh |
E415852
|
entity |
| Predicate | historicalUrbanFeatureType |
P80580
|
FINISHED |
| Object | market street or 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 street or square | Statement: [Koňský trh, historicalUrbanFeatureType, market street or square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalUrbanFeatureType Context triple: [Koňský trh, historicalUrbanFeatureType, market street or square]
-
A.
historicalStructure
Indicates that the subject is a structure recognized for its historical significance or heritage value.
-
B.
urbanHistoryFeature
chosen
Indicates a feature that plays a significant role in the historical development, events, or evolution of an urban area.
-
C.
capitalHistoric
Indicates that a location has served as a capital city at some point in history, even if it is not the current capital.
-
D.
historicLocationType
Indicates the specific kind or category of a place based on its historical significance or role.
-
E.
historicalSettlementType
Indicates the type or category of settlement an entity was historically classified as (e.g., village, town, city) during a past period.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2cf1c588190986167adcf4851b5 |
completed | April 18, 2026, 9:08 p.m. |
| PD | Predicate disambiguation | batch_69e3830192ac819091344a9e5a36c8c9 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:36 a.m.