Triple
T38294022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanškroun, Czechoslovakia |
E1022440
|
entity |
| Predicate | hasCurrentCountryName |
P174261
|
FINISHED |
| Object | Czech Republic |
—
|
NE NERFINISHED |
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: Czech Republic | Statement: [Lanškroun, Czechoslovakia, hasCurrentCountryName, Czech Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCurrentCountryName Context triple: [Lanškroun, Czechoslovakia, hasCurrentCountryName, Czech Republic]
-
A.
hasAssignedCountryName
Indicates that an entity is associated with a specific country through an assigned country name.
-
B.
appliedToCurrentCountry
Indicates that something (such as a rule, setting, or operation) is applied specifically to the country that is currently in context.
-
C.
presentNameCountry
chosen
Indicates that an entity is currently known or referred to by a specific country name.
-
D.
hasNameUsageCountry
Indicates that a particular name is used or recognized within a specified country.
-
E.
hasCountryContext
Indicates that something is associated with, interpreted within, or relevant to a specific country or national context.
- 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_69f76df190f081908d5aa02c8a9286d0 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
Created at: May 3, 2026, 4:30 p.m.