Triple
T19014784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl Monroe |
E465317
|
entity |
| Predicate | scoringTitleCollege |
P98738
|
FINISHED |
| Object | 1966–67 NCAA Division II scoring leader |
—
|
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: 1966–67 NCAA Division II scoring leader | Statement: [Earl Monroe, scoringTitleCollege, 1966–67 NCAA Division II scoring leader]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoringTitleCollege Context triple: [Earl Monroe, scoringTitleCollege, 1966–67 NCAA Division II scoring leader]
-
A.
collegeScoringRecord
chosen
Indicates that an entity holds or represents a record for scoring performance achieved during college-level competition.
-
B.
collegeScoringReputation
Indicates the perceived quality or effectiveness of a college’s ability to score points or perform offensively in its competitive context.
-
C.
namedForCollege
Indicates that an entity is named after or in honor of a particular college.
-
D.
scoredPointsPerGameInCollege
Indicates the average number of points an entity (typically an athlete) scored per game during their college career.
-
E.
nationalChampionshipTitle
Indicates that an entity has won a national-level championship title in a particular sport, competition, or field.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6d9f2a081908c0e923809da88e2 |
completed | April 20, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.