Triple
T34850371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Illiniwek |
E1004583
|
entity |
| Predicate | opponentView |
P140548
|
FINISHED |
| Object | racial stereotype |
—
|
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: racial stereotype | Statement: [Chief Illiniwek, opponentView, racial stereotype]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opponentView Context triple: [Chief Illiniwek, opponentView, racial stereotype]
-
A.
hasOpponentsView
chosen
Indicates that one entity holds, represents, or expresses the viewpoint or perspective of an opposing side in a conflict, debate, or competition.
-
B.
opponentInCase
Indicates that two parties are on opposing sides in the same legal case or proceeding.
-
C.
opponentState
Indicates the condition or status that an opposing party or competitor is currently in within a given context or interaction.
-
D.
opponentGroup
Indicates that one group is in opposition or conflict with another group, typically as a rival, competitor, or adversary.
-
E.
opponentInScenario
Indicates that one entity is an adversary or rival of another within a specific scenario, context, or situation.
- 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_69f76dba76f0819090643cba102c41ec |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.