Triple
T13687613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 NCAA Men’s Final Four |
E328171
|
entity |
| Predicate | championshipWinningShotType |
P30535
|
FINISHED |
| Object | buzzer-beating three-point field goal |
—
|
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: buzzer-beating three-point field goal | Statement: [2016 NCAA Men’s Final Four, championshipWinningShotType, buzzer-beating three-point field goal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championshipWinningShotType Context triple: [2016 NCAA Men’s Final Four, championshipWinningShotType, buzzer-beating three-point field goal]
-
A.
shotType
chosen
Indicates the specific kind or category of shot used or taken in a given context (e.g., in film, photography, or sports).
-
B.
championshipGameScore
Indicates the final score achieved by each participant in a championship game.
-
C.
nicknameOfShot
Indicates that one term is a nickname or informal name used to refer to a particular shot.
-
D.
MVPShotsOnGoal
Indicates that the entity identified as the MVP recorded a certain number of shots on goal in a game or competition.
-
E.
championshipGame
Indicates a game that determines the overall champion or winner of a competition or tournament.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc670968881908e2b4fdf656c7285 |
completed | April 12, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:53 p.m.