Triple
T2530208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6th Panzer Army |
E56138
|
entity |
| Predicate | resultInHungary |
P39402
|
FINISHED |
| Object | suffered heavy losses and retreated |
—
|
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: suffered heavy losses and retreated | Statement: [6th Panzer Army, resultInHungary, suffered heavy losses and retreated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultInHungary Context triple: [6th Panzer Army, resultInHungary, suffered heavy losses and retreated]
-
A.
result
Indicates that one entity is produced, caused, or brought about as an outcome or consequence of another entity or process.
-
B.
resultForFriedrichFlick
Indicates the outcome or decision rendered in relation to Friedrich Flick, such as a verdict, ruling, or final result concerning him.
-
C.
resultForGreatBritain
Indicates the outcome or performance achieved specifically by Great Britain in a given event, context, or measurement.
-
D.
resultForDutchRepublic
Indicates the outcome or consequence that pertains specifically to the Dutch Republic in a given event or context.
-
E.
resultDetermination
Indicates the process or criteria by which an outcome, decision, or result is established or concluded from given inputs or conditions.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd276930c8190bd46b52e06b7098e |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd18e72a88190bdcf12b326d42fad |
completed | March 7, 2026, 7:19 a.m. |
Created at: March 6, 2026, 9:46 p.m.