Triple
T1992671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terry Dischinger |
E43284
|
entity |
| Predicate | NBARookieSeason |
P31236
|
FINISHED |
| Object | 1962-1963 |
—
|
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: 1962-1963 | Statement: [Terry Dischinger, NBARookieSeason, 1962-1963]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NBARookieSeason Context triple: [Terry Dischinger, NBARookieSeason, 1962-1963]
-
A.
NBArookieOfTheYearAwards
Indicates that the subject has received one or more NBA Rookie of the Year awards.
-
B.
NBArookieOfTheYearSeason
chosen
Indicates the season in which a player received the NBA Rookie of the Year award.
-
C.
NBAAllRookieTeam
Indicates that a player was selected to the NBA All-Rookie Team for a given season.
-
D.
sharedRookieOfTheYearWith
Indicates that two entities were both awarded Rookie of the Year in the same season or context.
-
E.
enteredNBADirectlyFrom
Indicates that a player joined the NBA directly from the specified source (such as high school, overseas, or another non-collegiate path) without first playing college basketball.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.