Triple
T29501702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homer Bryce Stadium |
E748385
|
entity |
| Predicate | hasGoalPosts |
P124860
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Homer Bryce Stadium, hasGoalPosts, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGoalPosts Context triple: [Homer Bryce Stadium, hasGoalPosts, yes]
-
A.
hasFieldGoalPosts
chosen
Indicates that one entity possesses or is equipped with field goal posts, typically as part of a sports playing area.
-
B.
isGoalLineStand
Indicates that an entity is positioned or formed as a defensive stand at the goal line, typically to prevent an opposing score.
-
C.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
-
D.
hasEndZoneDesign
Indicates that an entity possesses a specific design or pattern applied to the end zone area of a playing field.
-
E.
hasOppositionGoal
Indicates that one entity’s goal is in direct conflict with, or aims to prevent the achievement of, another entity’s goal.
- 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_69f0bd455a9c8190b40a3e8ea38cf61f |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 28, 2026, 4:24 p.m.