Triple
T11803464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Rivers |
E280684
|
entity |
| Predicate | collegeStatistics |
P79019
|
FINISHED |
| Object | over 2,000 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: over 2,000 career points at Notre Dame | Statement: [David Rivers, collegeStatistics, over 2,000 career points at Notre Dame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeStatistics Context triple: [David Rivers, collegeStatistics, over 2,000 career points at Notre Dame]
-
A.
statisticsConsidered
Indicates that certain statistics are taken into account or used as a basis in a decision, analysis, or evaluation involving the related entities.
-
B.
statisticNote
Indicates that there is an explanatory note or comment providing additional context or clarification about a reported statistic.
-
C.
statisticalPurpose
Indicates that something is used for collecting, analyzing, or presenting data for statistical analysis or reporting purposes.
-
D.
statisticalType
Indicates that one entity specifies the kind or category of statistical characterization or measurement that applies to another entity.
-
E.
hasCollegeStatistics
chosen
Indicates that an entity possesses recorded statistical data related to its college-level performance or activities.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a658f918819092c2db05fe2ab0ce |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a24e9a088190aff7932d1ff93dbf |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.