Triple
T102366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl XXXVIII |
E2065
|
entity |
| Predicate | halftimeShowConsequence |
P812
|
FINISHED |
| Object | increased broadcast indecency regulation |
—
|
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: increased broadcast indecency regulation | Statement: [Super Bowl XXXVIII, halftimeShowConsequence, increased broadcast indecency regulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: halftimeShowConsequence Context triple: [Super Bowl XXXVIII, halftimeShowConsequence, increased broadcast indecency regulation]
-
A.
hasConsequence
chosen
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
B.
collapsedDuring
Indicates that one entity structurally failed or fell down while another specified event or process was occurring.
-
C.
endedConflict
Indicates that a previously ongoing conflict between entities has been brought to an end.
-
D.
after
Indicates that one event, state, or action occurs later in time than another, following it in temporal order.
-
E.
subsequentConflict
Indicates that one conflict occurs after and is temporally subsequent to another conflict.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2563a6ff48190bec582fb2f99b7af |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.