Triple
T1061198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanshin Koshien Stadium |
E22909
|
entity |
| Predicate | hasOutfieldFenceDistance |
P22064
|
FINISHED |
| Object | approximately 95 meters to the poles |
—
|
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: approximately 95 meters to the poles | Statement: [Hanshin Koshien Stadium, hasOutfieldFenceDistance, approximately 95 meters to the poles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOutfieldFenceDistance Context triple: [Hanshin Koshien Stadium, hasOutfieldFenceDistance, approximately 95 meters to the poles]
-
A.
outfieldWallDistance
chosen
Indicates the measured distance from home plate to the outfield wall at a particular point or area on the field.
-
B.
hasOutfieldFeature
Indicates that an entity possesses or includes a specific feature or characteristic located in its outfield area.
-
C.
gameWinningFieldGoalDistance
Indicates the distance from which a decisive, game-winning field goal was successfully kicked.
-
D.
distanceOfMissedFieldGoal
Indicates the yardage distance from which a field goal attempt was missed.
-
E.
hasBallpark
Indicates that an entity possesses, is associated with, or includes a specific ballpark as part of its attributes or facilities.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4ba6e35ac8190802341c31bda0e3b |
completed | March 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69a4b7340a048190807363f19d17a58f |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.