Triple
T15883621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WWE Divas Championship |
E385134
|
entity |
| Predicate | totalChampionsCount |
P120908
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [WWE Divas Championship, totalChampionsCount, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalChampionsCount Context triple: [WWE Divas Championship, totalChampionsCount, 17]
-
A.
titleTotalNumberForChampion
Indicates the total count of titles that a given champion has achieved.
-
B.
gameCountForChampion
Indicates the number of games that have been played involving a given champion.
-
C.
leagueChampionAL
Indicates that the subject entity is the champion (winner) of a specified league in a particular season or context.
-
D.
leagueChampionFranchisePennantCount
Indicates the number of league championship pennants won by a given franchise.
-
E.
leagueOfChampion
Indicates that an entity is the league or competition in which a given champion or titleholder competes or holds their status.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:51 a.m.