Triple
T16764496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prague 1 |
E407427
|
entity |
| Predicate | hasHighConcentrationOf |
P81830
|
FINISHED |
| Object | cultural monuments |
—
|
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: cultural monuments | Statement: [Prague 1, hasHighConcentrationOf, cultural monuments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighConcentrationOf Context triple: [Prague 1, hasHighConcentrationOf, cultural monuments]
-
A.
hasHighDensityOf
chosen
Indicates that one entity contains or exhibits a large concentration or amount of another entity within a given area, volume, or context.
-
B.
hasConcentration
Indicates that one entity possesses or exhibits a specific level, strength, or density of another substance, property, or attribute.
-
C.
concentration
Indicates the degree to which a substance or entity is present within a given medium, mixture, or space.
-
D.
hasHigh
Indicates that an entity possesses a high level, degree, or intensity of a specified attribute or property.
-
E.
concentrationVariant
Indicates that one entity represents a version or form of another that differs specifically in concentration level.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abef492c8190880d3b39c3641eed |
completed | April 18, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.