Triple
T316834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungarian 2nd Army |
E7725
|
entity |
| Predicate | sufferedLossesDuring |
P3824
|
FINISHED |
| Object | Soviet offensives around Stalingrad |
—
|
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: Soviet offensives around Stalingrad | Statement: [Hungarian 2nd Army, sufferedLossesDuring, Soviet offensives around Stalingrad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sufferedLossesDuring Context triple: [Hungarian 2nd Army, sufferedLossesDuring, Soviet offensives around Stalingrad]
-
A.
losses
Indicates that an entity experiences a decrease in value, quantity, or advantage as a result of some event or comparison.
-
B.
careerLosses
Indicates the total number of defeats or losses an entity has accumulated over the course of its entire career.
-
C.
loserPoints
Indicates the number of points awarded to or accumulated by the losing side in a competitive event or comparison.
-
D.
occurredDuring
chosen
Indicates that one event or action took place within the temporal span of another event or time period.
-
E.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
- 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.