Triple
T5006030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Winter Storm |
E112492
|
entity |
| Predicate | distanceFromStalingradPocketAtClosestPoint |
P60793
|
FINISHED |
| Object | approximately 50 kilometers |
—
|
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: approximately 50 kilometers | Statement: [Operation Winter Storm, distanceFromStalingradPocketAtClosestPoint, approximately 50 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromStalingradPocketAtClosestPoint Context triple: [Operation Winter Storm, distanceFromStalingradPocketAtClosestPoint, approximately 50 kilometers]
-
A.
locationDuringStalingrad
Indicates that an entity was located at a specific place during the time period of the Battle of Stalingrad.
-
B.
distanceFromSaintPetersburg
Indicates the spatial distance between a given entity and the city of Saint Petersburg.
-
C.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
-
D.
frontLineDistanceFromMoscow
Indicates the measured distance between the current front line of a conflict and the city of Moscow.
-
E.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd73089f548190834103366e24ab40 |
completed | March 20, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:35 p.m.