Triple
T3146311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2019 WNBA season |
E65771
|
entity |
| Predicate | ElenaDelleDonneThreePointPercentage |
P46372
|
FINISHED |
| Object | 43.0% |
—
|
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: 43.0% | Statement: [2019 WNBA season, ElenaDelleDonneThreePointPercentage, 43.0%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ElenaDelleDonneThreePointPercentage Context triple: [2019 WNBA season, ElenaDelleDonneThreePointPercentage, 43.0%]
-
A.
WNBAAllTimeScoringLeader
Indicates that the subject is recognized as the player with the highest total points scored in WNBA history.
-
B.
MVPThreePointersAttempted
Indicates the number of three-point shots attempted by the MVP in a given context or period.
-
C.
NBAThreePointContestTitles
Indicates the number of NBA Three-Point Contest championship titles an entity has won.
-
D.
usedThreePointLine
Indicates that an action or play involved or was executed from beyond the three-point line.
-
E.
goalsByMeganRapinoe
Indicates the scoring events (goals) that are attributed to Megan Rapinoe.
- 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada598ccf08190b8817c456f38f2d7 |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfa3d9081908425aa636bb9b897 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada148e9108190b363dd0f1a94ac8e |
completed | March 8, 2026, 4:18 p.m. |
Created at: March 8, 2026, 3:05 p.m.