Triple
T17360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Star-Spangled Banner |
E343
|
entity |
| Predicate | hasControversyAbout |
P494
|
FINISHED |
| Object | kneeling protests during performances |
—
|
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: kneeling protests during performances | Statement: [The Star-Spangled Banner, hasControversyAbout, kneeling protests during performances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasControversyAbout Context triple: [The Star-Spangled Banner, hasControversyAbout, kneeling protests during performances]
-
A.
hasNotableSubject
chosen
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
B.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
C.
hasNotableMember
Indicates that a group, organization, or collection includes at least one member who is distinguished or noteworthy in some significant way.
-
D.
officeContested
Indicates that a particular office or position is being actively sought or challenged by multiple parties in an election or selection process.
-
E.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242494a548190a5776fb6cad4d4af |
completed | Feb. 28, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69a23fedf0fc8190ad99bd1da297b14d |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.