Triple
T15767769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pine Tar Incident |
E382268
|
entity |
| Predicate | notableReaction |
P97670
|
FINISHED |
| Object | George Brett charged out of the dugout in anger |
—
|
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: George Brett charged out of the dugout in anger | Statement: [Pine Tar Incident, notableReaction, George Brett charged out of the dugout in anger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableReaction Context triple: [Pine Tar Incident, notableReaction, George Brett charged out of the dugout in anger]
-
A.
notableReception
Indicates that something has received significant attention, recognition, or response from audiences, critics, or the public.
-
B.
notableImpression
Indicates that one entity has made a significant or memorable impact on another entity.
-
C.
causedReaction
chosen
Indicates that one entity’s action or state brought about a specific reaction or response in another entity.
-
D.
relatedReaction
Indicates that one reaction is connected or associated with another reaction in some relevant way.
-
E.
notablePraise
Indicates that one entity has given significant or distinguished praise or commendation to another entity.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e051951bac8190a7d45f3612c6de72 |
completed | April 16, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.