Triple
T7821754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heinie Zimmerman |
E181145
|
entity |
| Predicate | gameNumberOfFamousRundown |
P79195
|
FINISHED |
| Object | Game 6 |
—
|
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: Game 6 | Statement: [Heinie Zimmerman, gameNumberOfFamousRundown, Game 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gameNumberOfFamousRundown Context triple: [Heinie Zimmerman, gameNumberOfFamousRundown, Game 6]
-
A.
hallOfFameNumber
Indicates the unique number assigned to an entity to denote its position or identifier within a Hall of Fame.
-
B.
famousProgram
Indicates that a program is widely recognized or well-known, typically for its impact, quality, or popularity.
-
C.
hallOfFamePlayersCount
Indicates the number of players associated with an entity who have been inducted into a hall of fame.
-
D.
famousLegend
Indicates that the subject is widely known and celebrated in stories, myths, or folklore, often with enduring cultural significance.
-
E.
gamesWonBy
Indicates the number of games that have been won by a particular entity in a given context.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cafa083fe88190a77efb7cfee4bd6f |
completed | March 30, 2026, 10:32 p.m. |
| PD | Predicate disambiguation | batch_69cae91ae008819098e56bbe51143b31 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:41 p.m.