Triple
T316846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungarian 2nd Army |
E7725
|
entity |
| Predicate | equipmentLevel |
P2086
|
FINISHED |
| Object | poorly equipped compared to German units |
—
|
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: poorly equipped compared to German units | Statement: [Hungarian 2nd Army, equipmentLevel, poorly equipped compared to German units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equipmentLevel Context triple: [Hungarian 2nd Army, equipmentLevel, poorly equipped compared to German units]
-
A.
technologyLevel
chosen
Indicates the degree of technological advancement or sophistication associated with an entity relative to others or to a defined scale.
-
B.
deviceIndicates
Indicates that a device provides a signal, status, or output that conveys information about a condition, event, or state.
-
C.
teamLevel
Indicates the hierarchical rank or tier at which a team operates within an organization, competition, or structure.
-
D.
amenityLevel
Indicates the degree or quality of facilities, services, or conveniences provided in relation to something.
-
E.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea65ca7081908093e6aaaf2d34f7 |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.