Triple
T82820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soldier Field |
E1663
|
entity |
| Predicate | hasScoreboards |
P2583
|
FINISHED |
| Object | video boards |
—
|
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: video boards | Statement: [Soldier Field, hasScoreboards, video boards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScoreboards Context triple: [Soldier Field, hasScoreboards, video boards]
-
A.
hasScoreboard
chosen
Indicates that one entity is equipped with or associated with a scoreboard used to display scores or results.
-
B.
hasScoreboardLocation
Indicates the spatial or logical position where a scoreboard is placed or associated within a given context.
-
C.
hasScoreboardType
Indicates the specific kind or category of scoreboard associated with an entity.
-
D.
hasBallpark
Indicates that an entity possesses, is associated with, or includes a specific ballpark as part of its attributes or facilities.
-
E.
finalScore
Indicates the resulting or overall score achieved after all contributing actions, events, or evaluations are completed.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.