Triple
T22213724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2006–07 NBA season |
E549019
|
entity |
| Predicate | scoringLeader |
P6605
|
FINISHED |
| Object | Kobe Bryant |
—
|
NE NERFINISHED |
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: Kobe Bryant | Statement: [2006–07 NBA season, scoringLeader, Kobe Bryant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobe Bryant Context triple: [2006–07 NBA season, scoringLeader, Kobe Bryant]
-
A.
Kobe Bryant
chosen
Kobe Bryant was an American professional basketball player, primarily with the Los Angeles Lakers, widely regarded as one of the greatest players in NBA history.
-
B.
Bryant
Bryant is a common English surname borne by numerous notable figures in American history, literature, sports, and public life.
-
C.
Bryant
Bryant is a suburban city in central Arkansas, United States, located near Little Rock.
-
D.
Bryant
Bryant is the middle name of James B. Conant, the influential American chemist, educator, and president of Harvard University.
-
E.
Bryant
Bryant is a residential neighborhood in northeast Seattle, Washington, known for its quiet streets, family-friendly atmosphere, and proximity to parks and schools.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3f7e04819089806d81d5ac431e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b2d607c81909511761b5563ddee |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:37 p.m.