Triple
T6625940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruhrkessel |
E149799
|
entity |
| Predicate | numberOfGermanTroopsEncircled |
P71592
|
FINISHED |
| Object | over 300000 |
—
|
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: over 300000 | Statement: [Ruhrkessel, numberOfGermanTroopsEncircled, over 300000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGermanTroopsEncircled Context triple: [Ruhrkessel, numberOfGermanTroopsEncircled, over 300000]
-
A.
dateOfCityEncirclement
Indicates the date on which a city became fully encircled, typically by military or blockade forces, cutting it off from external access.
-
B.
numberOfHoldersKilledInWorldWarII
Indicates the number of holders of a given title, position, or role who were killed during World War II.
-
C.
numberOfGermanVictims
Indicates the quantity of victims who are identified as German in the context of the described event or situation.
-
D.
estimatedNumberOfSurvivorsAtLiberation
Indicates the approximate count of individuals who were still alive at the time a camp or similar site was liberated.
-
E.
casualtiesAtStalingrad
Indicates that an entity experienced casualties (killed, wounded, or missing) in connection with the Battle of Stalingrad.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6bdb76ec48190b59d576170970cc9 |
completed | March 27, 2026, 5:26 p.m. |
Created at: March 27, 2026, 1:58 p.m.