Triple
T36387804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States women's national water polo team |
E896243
|
entity |
| Predicate | hasProducedOlympicMVPs |
P204851
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [United States women's national water polo team, hasProducedOlympicMVPs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProducedOlympicMVPs Context triple: [United States women's national water polo team, hasProducedOlympicMVPs, yes]
-
A.
NBA_MVP_awards
Indicates the number of times an entity has received the NBA Most Valuable Player (MVP) award.
-
B.
numberOfLeagueMVPawards
Indicates the count of times an entity has received the league’s Most Valuable Player (MVP) award.
-
C.
numberOfNBLMVPawards
Indicates the number of times an entity has received the NBL Most Valuable Player (MVP) award.
-
D.
MVPawardsWon
Indicates the number of Most Valuable Player (MVP) awards that an entity has received.
-
E.
mvpAwardAL
Indicates that a player has received the Most Valuable Player (MVP) award in the American League.
- 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_69f76e52e3108190becf70b090ae7bd6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:10 p.m.