Triple
T9078936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey McConnell |
E217563
|
entity |
| Predicate | hasCollegeStatisticsIn |
P79019
|
FINISHED |
| Object | assists |
—
|
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: assists | Statement: [Mickey McConnell, hasCollegeStatisticsIn, assists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCollegeStatisticsIn Context triple: [Mickey McConnell, hasCollegeStatisticsIn, assists]
-
A.
hasCollegeStatistics
chosen
Indicates that an entity possesses recorded statistical data related to its college-level performance or activities.
-
B.
playedCollegeSport
Indicates that the subject participated in an organized college-level sport for the object institution.
-
C.
scoredPointsPerGameInCollege
Indicates the average number of points an entity (typically an athlete) scored per game during their college career.
-
D.
playedForCollegeTeamFrom
Indicates that an individual was a member of and played for a specific college team starting in a given year.
-
E.
playedCollegeBasketballFor
Indicates that a person was a member of and competed for a specific college or university’s basketball team.
- 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_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc95c93ee48190842623b57e50f4cf |
completed | April 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:12 p.m.