Triple

T14229405
Position Surface form Disambiguated ID Type / Status
Subject dba (Deutsche BA) E352711 entity
Predicate callsign P1565 FINISHED
Object BAVARIA
BAVARIA is the radio callsign used by the former German regional airline Deutsche BA.
E1088818 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: BAVARIA | Statement: [dba (Deutsche BA), callsign, BAVARIA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BAVARIA
Context triple: [dba (Deutsche BA), callsign, BAVARIA]
  • A. Bavaria
    Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
  • B. Baier
    Baier is a surname most prominently associated with Bret Baier, the American television news anchor and host on Fox News.
  • C. Swabia (Bavaria)
    Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities and rural landscapes.
  • D. Saksa
    Saksa is a prominent mountain in Norway’s Sunnmøre Alps, known for its steep ascent and panoramic views over the Hjørundfjord.
  • E. Bavier
    Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
  • 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: BAVARIA
Triple: [dba (Deutsche BA), callsign, BAVARIA]
Generated description
BAVARIA is the radio callsign used by the former German regional airline Deutsche BA.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BAVARIA
Target entity description: BAVARIA is the radio callsign used by the former German regional airline Deutsche BA.
  • A. Bavaria
    Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
  • B. Baier
    Baier is a surname most prominently associated with Bret Baier, the American television news anchor and host on Fox News.
  • C. Swabia (Bavaria)
    Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities and rural landscapes.
  • D. Saksa
    Saksa is a prominent mountain in Norway’s Sunnmøre Alps, known for its steep ascent and panoramic views over the Hjørundfjord.
  • E. Bavier
    Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de622b89fc8190af08dab9e1976759 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3251ec5881909fcebc9477d6a761 completed May 8, 2026, 12:46 a.m.
NEDg Description generation batch_69fd3408af2481909ff159694ed2d767 completed May 8, 2026, 12:53 a.m.
NED2 Entity disambiguation (via description) batch_69fd3460d8e88190884e7d532645b79c completed May 8, 2026, 12:54 a.m.
Created at: April 10, 2026, 1:07 a.m.