Triple
T31720303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miroslav Tyrš |
E809557
|
entity |
| Predicate | hasCitizenshipDuringLifetime |
P31432
|
FINISHED |
| Object | Austrian Empire |
—
|
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: Austrian Empire | Statement: [Miroslav Tyrš, hasCitizenshipDuringLifetime, Austrian Empire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCitizenshipDuringLifetime Context triple: [Miroslav Tyrš, hasCitizenshipDuringLifetime, Austrian Empire]
-
A.
citizenshipDuringLifetime
chosen
Indicates that an entity held citizenship in a particular country or political unit at some point during its lifetime.
-
B.
hasAncestralCitizenshipOf
Indicates that an entity holds or is recognized as holding citizenship of another entity based on ancestral or lineage connections rather than solely on birth or residence.
-
C.
nationalityDuringLife
Indicates that a person held a particular nationality for some or all of their lifetime.
-
D.
hasBiographicalSubjectCitizenship
Indicates that the biographical subject holds or has held citizenship in the specified country or political entity.
-
E.
citizenshipGrantedYear
Indicates the specific year in which an entity was officially granted citizenship.
- 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_69f348e009c8819095d77df52c645b9c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 30, 2026, 11:18 p.m.