Triple
T25723310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States uniformed services ranks |
E645047
|
entity |
| Predicate | lowestRankCategory |
P34975
|
FINISHED |
| Object | junior enlisted ranks |
—
|
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: junior enlisted ranks | Statement: [United States uniformed services ranks, lowestRankCategory, junior enlisted ranks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowestRankCategory Context triple: [United States uniformed services ranks, lowestRankCategory, junior enlisted ranks]
-
A.
lowestCategory
chosen
Indicates that an entity belongs to the most specific or least general category within a classification hierarchy.
-
B.
lowestRank
Indicates that the subject has the least or worst rank in an ordered set compared to all other related entities.
-
C.
lowerRank
Indicates that one entity holds an inferior or subordinate rank, status, or position relative to another entity.
-
D.
lowestPeakInCategory
Indicates that an entity is the peak with the minimum height (or value) among all peaks within a specified category.
-
E.
lowestLevelLabel
Indicates that the subject is associated with the most specific or deepest-level label in a hierarchical labeling or classification structure.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc683cd48190bf4bab9cb8de691a |
completed | May 2, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 10:07 p.m.