Triple
T4730882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darrelle Revis |
E105002
|
entity |
| Predicate | allProSecondTeamSelectionCount |
P59080
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Darrelle Revis, allProSecondTeamSelectionCount, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allProSecondTeamSelectionCount Context triple: [Darrelle Revis, allProSecondTeamSelectionCount, 1]
-
A.
allProSelectionCount
Indicates the number of times an entity has been selected for an All-Pro team or equivalent top-level professional recognition.
-
B.
nflAllProSelection
Indicates that a player was selected to an NFL All-Pro team for a given season or time period.
-
C.
NFLTeamDraftedBy
Indicates that a particular NFL team selected a specific player in an official NFL draft.
-
D.
selectedToProBowl
Indicates that an athlete has been chosen to participate in the Pro Bowl all-star game.
-
E.
NBAAllNBASecondTeamSelections
Indicates the number of times an entity has been selected to the NBA All-NBA Second Team.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd67c895dc8190ba648002ff54424b |
completed | March 20, 2026, 3:29 p.m. |
Created at: March 20, 2026, 1:19 p.m.