Triple
T149773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Army officer ranks |
E3405
|
entity |
| Predicate | lowestRank |
P6063
|
FINISHED |
| Object | second lieutenant |
—
|
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: second lieutenant | Statement: [British Army officer ranks, lowestRank, second lieutenant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowestRank Context triple: [British Army officer ranks, lowestRank, second lieutenant]
-
A.
lowestPoint
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified context.
-
B.
highestRankIn
Indicates that one entity holds the top or most senior rank within a specified group, category, or context relative to other entities.
-
C.
nextHigherRank
Indicates that one entity holds the immediately superior rank or level in a hierarchy relative to another entity.
-
D.
rankedAs
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
-
E.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.