Triple
T8005769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ottmar Hitzfeld |
E186359
|
entity |
| Predicate | hasWonLeagueTitlesInMultipleCountries |
P80517
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ottmar Hitzfeld, hasWonLeagueTitlesInMultipleCountries, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWonLeagueTitlesInMultipleCountries Context triple: [Ottmar Hitzfeld, hasWonLeagueTitlesInMultipleCountries, true]
-
A.
consecutiveLeagueTitles
Indicates that one entity has won league titles in successive seasons without interruption.
-
B.
numberOfLeagueTitles
Indicates the total count of league championship titles that an entity has won.
-
C.
teamWithMultipleTitles
Indicates that a team has won more than one title or championship within the relevant competition or context.
-
D.
EuropeanChampionshipTitles
Indicates the number of European Championship titles an entity has won.
-
E.
numberOfTropheeDesChampionsTitles
Indicates the number of Trophée des Champions titles that an entity has won.
- F. None of above. chosen
Provenance (4 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3cf72fc08190aa78b97c1ab92f90 |
completed | March 31, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bcbbc0819094a98e7ffffb7a40 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:18 p.m.