Triple
T449034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Secretary |
E7085
|
entity |
| Predicate | appliesToRank |
P1129
|
FINISHED |
| Object | Cabinet-level official |
—
|
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: Cabinet-level official | Statement: [Mr. Secretary, appliesToRank, Cabinet-level official]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToRank Context triple: [Mr. Secretary, appliesToRank, Cabinet-level official]
-
A.
usesRank
Indicates that one entity applies or relies on a ranking or ordered level system associated with another entity.
-
B.
hasRankCategory
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
C.
typicallyHoldsRank
Indicates that an entity is most commonly or usually associated with holding a particular rank or level in a hierarchy.
-
D.
appliesTo
chosen
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
E.
associatedWithRank
Indicates a relationship where an entity is linked to a specific rank, level, or hierarchical position.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef6755a08190a057e72279b70456 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2ede1a1108190a4a06b3416ae6156 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.