Triple
T14816199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viktor Tikhonov |
E348320
|
entity |
| Predicate | EuropeanChampionshipTitlesAsCoach |
P13984
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Viktor Tikhonov, EuropeanChampionshipTitlesAsCoach, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EuropeanChampionshipTitlesAsCoach Context triple: [Viktor Tikhonov, EuropeanChampionshipTitlesAsCoach, multiple]
-
A.
championshipWonAsCoach
Indicates that the subject, acting in the role of coach, has won a championship title with the associated team or organization.
-
B.
numberOfWorldChampionsCoached
Indicates the count of distinct world champion individuals that a given coach has trained.
-
C.
UEFAChampionsLeagueTitlesAsManager
Indicates the number of UEFA Champions League titles a person has won specifically in the role of team manager.
-
D.
EuropeanChampionshipTitles
chosen
Indicates the number of European Championship titles an entity has won.
-
E.
conferenceChampionshipsWonAsCoach
Indicates the number of conference championship titles an individual has won while serving in the role of coach.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe2c1ec81908b3dff7a5d0e85d0 |
completed | April 14, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:49 a.m.