Triple
T11255172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Maravich |
E266417
|
entity |
| Predicate | collegeScoringRecord |
P98738
|
FINISHED |
| Object | NCAA Division I all-time leading scorer |
—
|
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: NCAA Division I all-time leading scorer | Statement: [Pete Maravich, collegeScoringRecord, NCAA Division I all-time leading scorer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeScoringRecord Context triple: [Pete Maravich, collegeScoringRecord, NCAA Division I all-time leading scorer]
-
A.
collegeCoach
Indicates that one entity serves as a coach for a college-level sports team associated with another entity.
-
B.
GreeneRank
Indicates a ranking or ordered position assigned according to Greene’s specific criteria or system.
-
C.
stateUniversity
Indicates that an institution is a university that is publicly funded and operated under the authority of a state or similar governmental entity.
-
D.
numberOfColleges
Indicates the quantity of colleges associated with a given entity.
-
E.
countryUniversity
Indicates that a university is located in, or belongs to, a particular country.
- 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.