Triple
T33281773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlsbad, Czech Republic |
E852063
|
entity |
| Predicate | hasHotSpringsCount |
P52851
|
FINISHED |
| Object | over 10 |
—
|
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: over 10 | Statement: [Carlsbad, Czech Republic, hasHotSpringsCount, over 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotSpringsCount Context triple: [Carlsbad, Czech Republic, hasHotSpringsCount, over 10]
-
A.
hasNumberOfHotSprings
chosen
Indicates the quantity of hot springs associated with a given entity.
-
B.
hasHotSpring
Indicates that one entity possesses, contains, or is associated with a hot spring.
-
C.
hasNumberOfMineralSprings
Indicates the relationship that specifies how many mineral springs are associated with a given entity.
-
D.
hasMineralSprings
Indicates that a place or entity possesses or is characterized by the presence of mineral springs.
-
E.
hasMineralSpringsType
Indicates that an entity is associated with or characterized by a specific type or category of mineral springs.
- 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_69f349653da08190819876015a298fdb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: May 1, 2026, 1:32 a.m.