Triple
T528375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elena Delle Donne |
E10973
|
entity |
| Predicate | numberOfWNBAAllStarSelections |
P15220
|
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: [Elena Delle Donne, numberOfWNBAAllStarSelections, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWNBAAllStarSelections Context triple: [Elena Delle Donne, numberOfWNBAAllStarSelections, multiple]
-
A.
WNBAFinalsAppearances
Indicates the number of times an entity has participated in the WNBA Finals series.
-
B.
wonWNBAChampionship
Indicates that an entity has achieved victory in the WNBA Finals and secured a WNBA championship title.
-
C.
NBAAllStarSelections
Indicates the number of times an individual has been selected to participate in the NBA All-Star Game.
-
D.
reachedWNBAFinals
Indicates that an entity (typically a team) advanced to and competed in the championship series of the WNBA season.
-
E.
NBAAllStarYears
Indicates the years in which a given player was selected as an NBA All-Star.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d39b4c81909f265b3501b5ec1d |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f01ac3ec8190a94a05955532c7fa |
completed | Feb. 28, 2026, 1:39 p.m. |
| PDg | Predicate description generation | batch_69a2f0dcff1881909c18e8c599c150a1 |
completed | Feb. 28, 2026, 1:42 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.