Triple
T33363756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Generalmajor |
E854292
|
entity |
| Predicate | comparativeRankUK |
P191822
|
FINISHED |
| Object | Brigadier (British Army, roughly) |
—
|
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: Brigadier (British Army, roughly) | Statement: [Generalmajor, comparativeRankUK, Brigadier (British Army, roughly)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comparativeRankUK Context triple: [Generalmajor, comparativeRankUK, Brigadier (British Army, roughly)]
-
A.
hasPopulationRankInUK
Indicates the relative position of an entity’s population size compared to other entities within the United Kingdom.
-
B.
depthRankInBritishIsles
Indicates the relative ordering of an entity by depth compared to other entities within the British Isles.
-
C.
comparableInternationalRank
Indicates that two entities have international rankings that can be meaningfully compared to each other.
-
D.
comparativeRankInUS
Indicates the relative ranking or position of an entity within the United States compared to other entities of the same type.
-
E.
relativeHeightRankInWales
Indicates the position of something in an ordered ranking based on its height relative to all comparable entities located in Wales.
- 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_69f3496bda8c8190bfc8fade9d1b791c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
| PDg | Predicate description generation | batch_69fcec5e560481909cd710b88897e833 |
completed | May 7, 2026, 7:47 p.m. |
Created at: May 1, 2026, 1:34 a.m.