Triple
T9563759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skylar Diggins-Smith |
E230738
|
entity |
| Predicate | collegeTeamPoints |
P89810
|
FINISHED |
| Object | 2000+ career points at Notre Dame |
—
|
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: 2000+ career points at Notre Dame | Statement: [Skylar Diggins-Smith, collegeTeamPoints, 2000+ career points at Notre Dame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeTeamPoints Context triple: [Skylar Diggins-Smith, collegeTeamPoints, 2000+ career points at Notre Dame]
-
A.
collegeTeamPointsPerGameLeader
Indicates the player who leads a college team in average points scored per game.
-
B.
collegeTeamPointsRecordHolder
Indicates that the subject is the record-holding individual or team for the highest number of points scored for a particular college team.
-
C.
collegeTeam
Indicates that one entity is a sports team that represents or is affiliated with a particular college or university.
-
D.
collegeChampionshipTeam
Indicates that a team is the winner of a specified college-level championship competition.
-
E.
collegeTeamChampionships
Indicates the championships or titles that a college sports team has won.
- 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9968b8608190b3078fe5764f0a69 |
completed | April 1, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69ccd594d0ac8190a81bc11a3a538167 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:04 p.m.