Triple
T25741936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | general broni |
E648241
|
entity |
| Predicate | comparativeRankInUS |
P163031
|
FINISHED |
| Object | lieutenant general (U.S.) |
—
|
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: lieutenant general (U.S.) | Statement: [general broni, comparativeRankInUS, lieutenant general (U.S.)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comparativeRankInUS Context triple: [general broni, comparativeRankInUS, lieutenant general (U.S.)]
-
A.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
-
B.
frequencyRankInUnitedStates
Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
-
C.
nationalRank
Indicates the position or standing of an entity within a ranking system at the national level.
-
D.
gdpRankInUS
Indicates the relative position of an entity in the ranking of U.S. entities based on their Gross Domestic Product (GDP).
-
E.
GreeneRank
Indicates a ranking or ordered position assigned according to Greene’s specific criteria or system.
- F. None of above. chosen
Provenance (4 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f63639a84c81909d700a539b458b42 |
completed | May 2, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69f63182f1408190bddc1214fcbd6145 |
completed | May 2, 2026, 5:16 p.m. |
| PDg | Predicate description generation | batch_69f6352df6148190bc10772cd40bd7b3 |
completed | May 2, 2026, 5:32 p.m. |
Created at: April 22, 2026, 3:45 a.m.