Triple
T426630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Medicine in Plzeň |
E9622
|
entity |
| Predicate | countryIsoCode |
P189
|
FINISHED |
| Object | CZ |
—
|
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: CZ | Statement: [Faculty of Medicine in Plzeň, countryIsoCode, CZ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryIsoCode Context triple: [Faculty of Medicine in Plzeň, countryIsoCode, CZ]
-
A.
ISOCode
Indicates that an entity is associated with a specific standardized code defined by the International Organization for Standardization (ISO).
-
B.
UNLOCODECountryCode
Indicates that an entity is associated with a specific country code as defined by the UN/LOCODE standard.
-
C.
countryDeJure
Indicates that one entity is the legally recognized (de jure) country having sovereignty or authority over another entity.
-
D.
hasISOCode
chosen
Indicates that an entity is associated with a specific standardized ISO code that uniquely identifies it according to ISO conventions.
-
E.
countryOrTerritory
Indicates that one entity is a country or territory associated with, or characterized by, another entity.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eed691c4819092b7e57306114bbc |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd6736c81909a6ca549f77b4345 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.