Triple
T3859191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago Bears–Green Bay Packers rivalry |
E90092
|
entity |
| Predicate | firstMeetingResult |
P36160
|
FINISHED |
| Object | Chicago Bears 20–0 Green Bay Packers |
—
|
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: Chicago Bears 20–0 Green Bay Packers | Statement: [Chicago Bears–Green Bay Packers rivalry, firstMeetingResult, Chicago Bears 20–0 Green Bay Packers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMeetingResult Context triple: [Chicago Bears–Green Bay Packers rivalry, firstMeetingResult, Chicago Bears 20–0 Green Bay Packers]
-
A.
firstMeetingScore
chosen
Indicates the evaluated quality or outcome of an entity’s initial meeting or first interaction with another entity.
-
B.
firstMeetingSeason
Indicates the season of the year during which two entities first met.
-
C.
initialReception
Indicates the nature or quality of the first response or reaction something receives when it is introduced or presented.
-
D.
firstMeetingYear
Indicates the calendar year in which two entities first met or had their initial encounter.
-
E.
initialOutcome
Indicates the result or state that first occurs at the beginning of a process, event, or interaction, before any subsequent changes or outcomes.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1ff39c8190b83a88abd840a0e3 |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.