Triple
T1087546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonny Jurgensen |
E24085
|
entity |
| Predicate | championshipsWon |
P313
|
FINISHED |
| Object | NFL Championship 1960 |
—
|
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: NFL Championship 1960 | Statement: [Sonny Jurgensen, championshipsWon, NFL Championship 1960]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championshipsWon Context triple: [Sonny Jurgensen, championshipsWon, NFL Championship 1960]
-
A.
hasChampionships
chosen
Indicates that one entity possesses or has won one or more championships associated with another entity.
-
B.
majorChampionshipWins
Indicates the number of major championship titles an entity has won.
-
C.
championshipRecognition
Indicates formal acknowledgment that an entity has won or holds a championship title in a given competition or domain.
-
D.
worldChampionshipTitles
Indicates the number of world championship titles an entity has won.
-
E.
careerWins
Indicates the total number of wins an individual or entity has accumulated over the course of their entire career.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b7407914819092ed933a7316b450 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.