Triple
T35928327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimní stadion Ivana Hlinky |
E1039084
|
entity |
| Predicate | namedAfterPersonNationality |
P36990
|
FINISHED |
| Object | Czech |
—
|
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: Czech | Statement: [Zimní stadion Ivana Hlinky, namedAfterPersonNationality, Czech]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterPersonNationality Context triple: [Zimní stadion Ivana Hlinky, namedAfterPersonNationality, Czech]
-
A.
namedAfterCountryOfNamesake
Indicates that something is named after a person or entity whose own name is derived from a particular country.
-
B.
namedForNationality
Indicates that something is named after or in reference to a particular nationality or national identity.
-
C.
namedAfterCountryLeaderOf
Indicates that one entity is named after a person who is or was the leader of a specific country.
-
D.
hasNamedAfterPerson
Indicates that one entity is named in honor of, or derived from the name of, a specific person.
-
E.
namedForNationalityOfHonouree
chosen
Indicates that something is named in honor of a person, specifically referencing that person's nationality.
- 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_69f76e23e4688190a5369138755138bf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 3, 2026, 4:07 p.m.