Triple
T6146904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Wiggins |
E137099
|
entity |
| Predicate | recruitingRanking |
P69444
|
FINISHED |
| Object | top high school prospect in class of 2013 |
—
|
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: top high school prospect in class of 2013 | Statement: [Andrew Wiggins, recruitingRanking, top high school prospect in class of 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recruitingRanking Context triple: [Andrew Wiggins, recruitingRanking, top high school prospect in class of 2013]
-
A.
selectionRankingEndPoint
Indicates the position or boundary in an ordered list at which a selection or ranking process concludes.
-
B.
educationRanking
Indicates the relative position or level assigned to an entity based on the quality or performance of its educational attributes or outcomes.
-
C.
springRank
Indicates a ranking relationship where entities are ordered or positioned relative to each other based on a spring-like or force-directed hierarchy or influence measure.
-
D.
rankingScope
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
E.
recruitingReputation
Indicates the perceived quality or effectiveness of an entity’s ability to attract and hire desirable candidates.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cdeeaa88190948d9db6eb2dbf46 |
completed | March 22, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69c055f39e0881909ae56444b1b48929 |
completed | March 22, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69c056c87340819088003f427706ebf8 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:16 p.m.