Triple
T15972303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Misty May-Treanor |
E387353
|
entity |
| Predicate | FIVBTitleCount |
P25122
|
FINISHED |
| Object | multiple FIVB World Tour event wins |
—
|
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 FIVB World Tour event wins | Statement: [Misty May-Treanor, FIVBTitleCount, multiple FIVB World Tour event wins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FIVBTitleCount Context triple: [Misty May-Treanor, FIVBTitleCount, multiple FIVB World Tour event wins]
-
A.
winnerTitleCount
chosen
Indicates the number of titles or championships an entity has won.
-
B.
numberOfLeagueTitles
Indicates the total count of league championship titles that an entity has won.
-
C.
worldTitles
Indicates that an entity has won one or more world championship titles in a given field or competition.
-
D.
FIFAFutsalWorldCupTitles
Indicates the number of FIFA Futsal World Cup championship titles an entity has won.
-
E.
numberOfDFBPokalTitles
Indicates the number of DFB-Pokal titles that an entity 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.