Triple
T28068506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Star Belgrade |
E709321
|
entity |
| Predicate | homeCountryCupTitles |
P41358
|
FINISHED |
| Object | multiple national cups |
—
|
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 national cups | Statement: [Red Star Belgrade, homeCountryCupTitles, multiple national cups]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCountryCupTitles Context triple: [Red Star Belgrade, homeCountryCupTitles, multiple national cups]
-
A.
nationalTeamTitles
Indicates the number of titles or championships an entity has won while representing its national team.
-
B.
homeCountryLeagueTitleRecord
Indicates the record or count of league titles an entity has won in its home country’s primary league competition.
-
C.
homeCountryTeamMatches
Indicates that the matches involve the team representing its own home country.
-
D.
domesticCupTitles
chosen
Indicates the number of national (in-country) cup competitions a team or club has won.
-
E.
nationalTeamTitleCount
Indicates the number of titles or championships a national team has won.
- 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_69ef9b6f8078819098b741274cd1a2ee |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 8:44 p.m.