Triple
T19985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White House Chief of Staff |
E397
|
entity |
| Predicate | isUsually |
P637
|
FINISHED |
| Object | most senior political appointee in the White House |
—
|
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: most senior political appointee in the White House | Statement: [White House Chief of Staff, isUsually, most senior political appointee in the White House]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsually Context triple: [White House Chief of Staff, isUsually, most senior political appointee in the White House]
-
A.
isAbout
Indicates that one entity has as its subject, focus, or primary concern the content, topic, or theme represented by another entity.
-
B.
is
chosen
Indicates that two entities are equivalent, share an attribute, or stand in a specified state or relation to each other.
-
C.
isPopularWith
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
D.
isSubjectTo
Indicates that one entity is governed, affected, or constrained by the authority, rules, conditions, or influence of another entity.
-
E.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.