Triple
T11255171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Maravich |
E266417
|
entity |
| Predicate | collegeCareerPoints |
P98737
|
FINISHED |
| Object | 3667 |
—
|
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: 3667 | Statement: [Pete Maravich, collegeCareerPoints, 3667]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeCareerPoints Context triple: [Pete Maravich, collegeCareerPoints, 3667]
-
A.
collegeCareerStart
Indicates the time or event at which an individual begins their college-level academic career.
-
B.
studCareer
Indicates that a student is pursuing or associated with a particular academic or professional career path.
-
C.
studCareerStart
Indicates the point in time when a student's professional or academic career begins.
-
D.
collegeCareerPeriod
Indicates the time span during which an individual is engaged in their college or university education and related academic activities.
-
E.
careerTackles
Indicates the total number of tackles a player has made over the course of their entire career.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9346f4c8190b29c2cf3a29cd1d1 |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d78793c00481908a3f764b610b77a4 |
completed | April 9, 2026, 11:03 a.m. |
| PDg | Predicate description generation | batch_69d796cf74308190a5b29d0dd82954a2 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:31 p.m.