Triple

T4819660
Position Surface form Disambiguated ID Type / Status
Subject Proskurov–Chernovtsy Offensive E107677 entity
Predicate opposedBy P437 FINISHED
Object Erich Model
Erich Model was a German military commander, likely a Wehrmacht officer, who played a role in opposing Soviet operations on the Eastern Front during World War II.
 E471955 NE FINISHED

How this triple was built (4 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: Erich Model | Statement: [Proskurov–Chernovtsy Offensive, opposedBy, Erich Model]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Erich Model
Context triple: [Proskurov–Chernovtsy Offensive, opposedBy, Erich Model]
  • A. Erich
    Erich is a masculine given name of German origin, commonly used in German-speaking countries and beyond.
  • B. Morgenstern
    Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
  • C. Uhlenbeck
    Uhlenbeck is a surname most prominently associated with Karen Uhlenbeck, a pioneering American mathematician and the first woman to receive the Abel Prize.
  • D. Neumann
    Neumann is a variant spelling of the surname Newman, commonly of German origin and borne by various notable figures in science, mathematics, and the arts.
  • E. Günther
    Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Erich Model
Triple: [Proskurov–Chernovtsy Offensive, opposedBy, Erich Model]
Generated description
Erich Model was a German military commander, likely a Wehrmacht officer, who played a role in opposing Soviet operations on the Eastern Front during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Erich Model
Target entity description: Erich Model was a German military commander, likely a Wehrmacht officer, who played a role in opposing Soviet operations on the Eastern Front during World War II.
  • A. Erich
    Erich is a masculine given name of German origin, commonly used in German-speaking countries and beyond.
  • B. Morgenstern
    Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
  • C. Uhlenbeck
    Uhlenbeck is a surname most prominently associated with Karen Uhlenbeck, a pioneering American mathematician and the first woman to receive the Abel Prize.
  • D. Neumann
    Neumann is a variant spelling of the surname Newman, commonly of German origin and borne by various notable figures in science, mathematics, and the arts.
  • E. Günther
    Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
  • F. None of above. chosen

Provenance (5 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_69bd43f9efa081908314cb3e94fa1695 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c98358081908ed43425af667a98 completed March 20, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4dbbfe588190bae0aca210bea2bc completed March 21, 2026, 7:50 a.m.
NEDg Description generation batch_69be4f6ceb60819080dc1ee93950a7f0 completed March 21, 2026, 7:57 a.m.
NED2 Entity disambiguation (via description) batch_69be4fbc83188190af2c9767aa9272a7 completed March 21, 2026, 7:58 a.m.
Created at: March 20, 2026, 1:24 p.m.