Triple
T38211685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rashaad Armein Penny |
E1010562
|
entity |
| Predicate | hasNumberInNFL |
P199517
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Rashaad Armein Penny, hasNumberInNFL, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberInNFL Context triple: [Rashaad Armein Penny, hasNumberInNFL, 20]
-
A.
yearsActiveInNFL
Indicates the span of time, measured in years, during which an entity actively participated in the NFL.
-
B.
nflId
Indicates a unique identifier assigned to an NFL player or entity within the dataset, used to distinguish it from all others.
-
C.
spentEntireNflCareerWith
Indicates that an NFL player spent their whole professional NFL career playing for a single team, without ever joining another NFL franchise.
-
D.
formerNFLPlayerAssociated
Indicates that a person was previously an NFL player and has or had some form of association or connection with another entity (such as a team, organization, or individual).
-
E.
joinedNFL
Indicates that an entity became a member of, or started playing in, the National Football League (NFL).
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff3fb2318c81908a46c2f513608935 |
completed | May 9, 2026, 2:07 p.m. |
| PD | Predicate disambiguation | batch_69ff3e96dcc48190819f6204680d84aa |
completed | May 9, 2026, 2:03 p.m. |
| PDg | Predicate description generation | batch_69ff3fb151008190bf8a90f9f1c5f0c8 |
completed | May 9, 2026, 2:07 p.m. |
Created at: May 3, 2026, 4:30 p.m.